{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "863f7f0a",
   "metadata": {},
   "source": [
    "Replication code for the paper:\n",
    "<br>Gulczyński, M., 2025, \"Sexism as a Predictor of Political Attitudes and Voting Behaviour. A Systematic Review\", Public Opinion Quarterly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a85110ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8dc4508f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('Gulczynski 24-0253.R1 Supplementary Material.xlsx', sheet_name=\"List_of_papers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b4d5068a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "97\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "USA                                     75\n",
       "New Zealand                              3\n",
       "Australia                                2\n",
       "Spain                                    2\n",
       "UK                                       2\n",
       "Canada                                   2\n",
       "Poland and Thailand                      1\n",
       "Italy                                    1\n",
       "Russia                                   1\n",
       "Brazil                                   1\n",
       "Spain (Catalonia)                        1\n",
       "Chile                                    1\n",
       "Korea                                    1\n",
       "Australia and USA                        1\n",
       "Germany, Norway, Sweden, Switzerland     1\n",
       "Sweden                                   1\n",
       "Japan                                    1\n",
       "Name: Countries under study, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = 'Countries under study'\n",
    "print(df[c].value_counts().sum())\n",
    "df[c].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f9fa2f71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Papers until 2016: 13\n",
      "Papers after 2016: 84\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1997     1\n",
       "2009     2\n",
       "2010     2\n",
       "2011     2\n",
       "2012     1\n",
       "2014     3\n",
       "2016     2\n",
       "2017     5\n",
       "2018     8\n",
       "2019    12\n",
       "2020     8\n",
       "2021    16\n",
       "2022    20\n",
       "2023    13\n",
       "2024     2\n",
       "Name: Year, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = 'Year'\n",
    "print(\"Papers until 2016:\",(df[c]<=2016).sum())\n",
    "print(\"Papers after 2016:\",(df[c]>2016).sum())\n",
    "df[c].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8aefc85b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vote for Trump                                                                                                                         12\n",
       "Abortion attitudes                                                                                                                      7\n",
       "Support for gender quota                                                                                                                3\n",
       "Favorability toward Clinton and Trump                                                                                                   2\n",
       "Vote for Clinton                                                                                                                        2\n",
       "                                                                                                                                       ..\n",
       "Candidate evaluation (including Biden, Harris, Warren) (four criteria: best representation, policy positions, electability, liking)     1\n",
       "Liberal feminist ideology                                                                                                               1\n",
       "Attitudes toward Clinton and Trump (presidential qualities)                                                                             1\n",
       "Vote for a fictitious female candidate in state legislative primary elections                                                           1\n",
       "Voter turnout\\nEngagement with political campaigns                                                                                      1\n",
       "Name: Outcome variables, Length: 76, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = 'Outcome variables'\n",
    "df[c].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a654f8bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "97\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Benevolent sexism\\nHostile sexism                                                                                         25\n",
       "Modern sexism                                                                                                             21\n",
       "Hostile sexism                                                                                                            15\n",
       "Hostile sexism\\nModern sexism                                                                                              7\n",
       "Sexism                                                                                                                     5\n",
       "Explicit:\\n1) Hostile sexism\\n2) Benevolent sexism\\n\\nImplicit sexism                                                      2\n",
       "Hostile sexism\\nBenevolent sexism                                                                                          2\n",
       "Modern sexism\\nTraditional sexism                                                                                          2\n",
       "Benevolent sexism\\nHostile sexism\\nModern sexism                                                                           2\n",
       "Benevolent sexism                                                                                                          1\n",
       "Hostile sexism\\nBenevolent sexism\\nModern sexism                                                                           1\n",
       "Politically defined\\nDomestically defined                                                                                  1\n",
       "Neosexism\\nImplicit bias                                                                                                   1\n",
       "Explicit sexism\\nImplicit sexism                                                                                           1\n",
       "Ambivalent sexism\\nBenevolent sexism\\nHostile sexism\\nSeparate Sphere Ideology (\"as an alternative measure of sexism\")     1\n",
       "Benevolent sexism \\nHostile sexism \\nBenevolent sexism toward men\\nHostile sexism toward men                               1\n",
       "Sexism\\nHostile sexism\\nModern sexism                                                                                      1\n",
       "Hostile sexism (called Sexism)                                                                                             1\n",
       "Modern sexism\\nNeosexism                                                                                                   1\n",
       "Sexism, including items from modern sexism, hostile sexism and attitudes towards feminists.                                1\n",
       "Ambivalent sexism                                                                                                          1\n",
       "Benevolent sexism toward men\\nHostile sexism toward men                                                                    1\n",
       "Modern sexism\\nAmbivalent sexism (not specified)                                                                           1\n",
       "Ambivalent sexism\\nBenevolent sexism\\nHostile sexism                                                                       1\n",
       "Benevolent sexism (Protective paternalism)\\nHostile sexism                                                                 1\n",
       "Name: Sexism concepts, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Frequency of sexism concepts\n",
    "\n",
    "c = 'Sexism concepts'\n",
    "print(df[c].value_counts().sum())\n",
    "df[c].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a727001a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Contains hostile: 62\n",
      "Contains benevolent: 38\n",
      "Contains modern: 37\n",
      "Contains implicit: 4\n",
      "Contains traditional: 2\n",
      "Contains neosexism: 2\n",
      "Contains hostile and benevolent: 37\n",
      "Contains hostile and modern: 12\n",
      "Contains modern and benevolent: 3\n",
      "Contains modern, benevolent, and hostile: 3\n",
      "Contains ambivalent: 4\n",
      "Contains Sexism: 8\n"
     ]
    }
   ],
   "source": [
    "df['concept_low'] = df['Sexism concepts'].str.lower()\n",
    "\n",
    "c = 'concept_low'\n",
    "print(\"Contains hostile:\",len(df[(df[c].str.contains('hostile'))]))\n",
    "print(\"Contains benevolent:\",len(df[(df[c].str.contains('benevolent'))]))\n",
    "print(\"Contains modern:\",len(df[(df[c].str.contains('modern'))]))\n",
    "print(\"Contains implicit:\",len(df[(df[c].str.contains('implicit'))]))\n",
    "print(\"Contains traditional:\",len(df[(df[c].str.contains('traditional'))]))\n",
    "print(\"Contains neosexism:\",len(df[(df[c].str.contains('neosexism'))]))\n",
    "print(\"Contains hostile and benevolent:\",len(df[(df[c].str.contains('hostile')) & df[c].str.contains('benevolent')]))\n",
    "print(\"Contains hostile and modern:\",len(df[(df[c].str.contains('hostile')) & df[c].str.contains('modern')]))\n",
    "print(\"Contains modern and benevolent:\",len(df[(df[c].str.contains('modern')) & df[c].str.contains('benevolent')]))\n",
    "print(\"Contains modern, benevolent, and hostile:\",len(df[(df[c].str.contains('modern')) & (df[c].str.contains('benevolent')) & (df[c].str.contains('hostile'))]))\n",
    "print(\"Contains ambivalent:\",len(df[(df[c].str.contains('ambivalent'))]))\n",
    "print(\"Contains Sexism:\",len(df[(df['Sexism concepts'].str.contains('Sexism'))]))\n",
    "\n",
    "# In the paper, 1 is deducted from hostile and benevolent sexism because Russo et al. 2014 use only sexism toward men (AMI)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "30ccb91e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Author</th>\n",
       "      <th>Title</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Countries under study</th>\n",
       "      <th>Elections (if any)</th>\n",
       "      <th>Time under study</th>\n",
       "      <th>Data sets</th>\n",
       "      <th>Outcome variables</th>\n",
       "      <th>Sexism concepts</th>\n",
       "      <th>Sexism items</th>\n",
       "      <th>Main findings</th>\n",
       "      <th>Theoretical mechanism linking sexism to outcome</th>\n",
       "      <th>Ambivalent sexism</th>\n",
       "      <th>Benevolent sexism</th>\n",
       "      <th>Hostile sexism</th>\n",
       "      <th>Modern sexism</th>\n",
       "      <th>Neosexism</th>\n",
       "      <th>concept_low</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018</td>\n",
       "      <td>Prusaczyk, Elvira; Hodson, Gordon</td>\n",
       "      <td>Left-right differences in abortion policy supp...</td>\n",
       "      <td>Personality and Individual Differences</td>\n",
       "      <td>USA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Abortion attitudes</td>\n",
       "      <td>Hostile sexism (called Sexism)</td>\n",
       "      <td>\"Many women interpret innocent remarks or acts...</td>\n",
       "      <td>\"the indirect effect of sexism was smaller tha...</td>\n",
       "      <td>From the Social Identity Theory (Tajfel &amp; Turn...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism (called sexism)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2021</td>\n",
       "      <td>Buyuker, Beyza; Durso, Amanda Jadidi; Filindra...</td>\n",
       "      <td>Race politics research and the American presid...</td>\n",
       "      <td>Journal of Race, Ethnicity and Politics</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and Republican primary</td>\n",
       "      <td>2016-2020</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>In Appendix E, not found online.\\n\\n\"We produc...</td>\n",
       "      <td>\"The effects of racial resentment and sexism w...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2021</td>\n",
       "      <td>Enders, Adam M.; Uscinski, Joseph E.</td>\n",
       "      <td>On Modeling the Social-Psychological Foundatio...</td>\n",
       "      <td>American Politics Research</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES 2016 and CCES 2018</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>CCES\\n1) _x0007_Women should earn the same wag...</td>\n",
       "      <td>a \"profile—an amalgamation of attitudes about,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2021</td>\n",
       "      <td>Filindra, Alexandra; Kaplan, Noah J.; Buyuker,...</td>\n",
       "      <td>Racial Resentment or Sexism? White Americans’ ...</td>\n",
       "      <td>Sociological Inquiry</td>\n",
       "      <td>USA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2008-2020</td>\n",
       "      <td>ANES and Gun Survey</td>\n",
       "      <td>\"Gun ownership, rationales for owning firearms...</td>\n",
       "      <td>Sexism, including items from modern sexism, ho...</td>\n",
       "      <td>Recently there has been a lot of talk about wo...</td>\n",
       "      <td>\"relationship between sexism and gun ownership...</td>\n",
       "      <td>Via gender ideologies, masculinist ideologies,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism, including items from modern sexism, ho...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2021</td>\n",
       "      <td>Hanley, Eric</td>\n",
       "      <td>Sexism as a political force: The impact of gen...</td>\n",
       "      <td>Social Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012 and 2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump and Romney</td>\n",
       "      <td>Sexism\\nHostile sexism\\nModern sexism</td>\n",
       "      <td>1. Media should pay less attention to discrimi...</td>\n",
       "      <td>\"Sexist orientations had a greater impact on h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism\\nhostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2021</td>\n",
       "      <td>Utych, Stephen M.</td>\n",
       "      <td>Sexism predicts favorability of women in the 2...</td>\n",
       "      <td>Electoral Studies</td>\n",
       "      <td>USA</td>\n",
       "      <td>Democratic primary</td>\n",
       "      <td>2019</td>\n",
       "      <td>VOTER survey</td>\n",
       "      <td>Attitudes towards real female or male candidat...</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>\"Women should return to their traditional role...</td>\n",
       "      <td>Sexism is a negative predictor of favorability...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2022</td>\n",
       "      <td>Bills, Matthew A.; Hayes, Brittany E.</td>\n",
       "      <td>The Association between Adherence to Sexist Be...</td>\n",
       "      <td>Journal of Homosexuality</td>\n",
       "      <td>USA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Attitudes toward sexual minorities</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>(1) Many women interpret innocent remarks or a...</td>\n",
       "      <td>\"Individuals with a stronger adherence to sexi...</td>\n",
       "      <td>People with sexist beliefs can have more negat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2023</td>\n",
       "      <td>Bauer, Nichole M.</td>\n",
       "      <td>Gendered Ambivalence: The Structure of Attitud...</td>\n",
       "      <td>Journal of Women, Politics and Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and parliamentary</td>\n",
       "      <td>1992-2000 and 2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Ambivalent attitudes toward candidates (Trump ...</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>ANES 1992-2000:\\ncloser to the equal role (1) ...</td>\n",
       "      <td>attitudinal ambivalence toward female candidat...</td>\n",
       "      <td>\"Individuals who hold sexist attitudes should ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year                                             Author  \\\n",
       "22  2018                  Prusaczyk, Elvira; Hodson, Gordon   \n",
       "50  2021  Buyuker, Beyza; Durso, Amanda Jadidi; Filindra...   \n",
       "52  2021               Enders, Adam M.; Uscinski, Joseph E.   \n",
       "53  2021  Filindra, Alexandra; Kaplan, Noah J.; Buyuker,...   \n",
       "55  2021                                       Hanley, Eric   \n",
       "61  2021                                  Utych, Stephen M.   \n",
       "68  2022              Bills, Matthew A.; Hayes, Brittany E.   \n",
       "82  2023                                  Bauer, Nichole M.   \n",
       "\n",
       "                                                Title  \\\n",
       "22  Left-right differences in abortion policy supp...   \n",
       "50  Race politics research and the American presid...   \n",
       "52  On Modeling the Social-Psychological Foundatio...   \n",
       "53  Racial Resentment or Sexism? White Americans’ ...   \n",
       "55  Sexism as a political force: The impact of gen...   \n",
       "61  Sexism predicts favorability of women in the 2...   \n",
       "68  The Association between Adherence to Sexist Be...   \n",
       "82  Gendered Ambivalence: The Structure of Attitud...   \n",
       "\n",
       "                                    Journal Countries under study  \\\n",
       "22   Personality and Individual Differences                   USA   \n",
       "50  Journal of Race, Ethnicity and Politics                   USA   \n",
       "52               American Politics Research                   USA   \n",
       "53                     Sociological Inquiry                   USA   \n",
       "55                 Social Science Quarterly                   USA   \n",
       "61                        Electoral Studies                   USA   \n",
       "68                 Journal of Homosexuality                   USA   \n",
       "82    Journal of Women, Politics and Policy                   USA   \n",
       "\n",
       "                     Elections (if any)    Time under study  \\\n",
       "22                                  NaN                2016   \n",
       "50  Presidential and Republican primary           2016-2020   \n",
       "52                         Presidential                2016   \n",
       "53                                  NaN           2008-2020   \n",
       "55                         Presidential       2012 and 2016   \n",
       "61                   Democratic primary                2019   \n",
       "68                                  NaN                2016   \n",
       "82       Presidential and parliamentary  1992-2000 and 2016   \n",
       "\n",
       "                  Data sets  \\\n",
       "22                     ANES   \n",
       "50                     ANES   \n",
       "52  ANES 2016 and CCES 2018   \n",
       "53      ANES and Gun Survey   \n",
       "55                     ANES   \n",
       "61             VOTER survey   \n",
       "68                     ANES   \n",
       "82                     ANES   \n",
       "\n",
       "                                    Outcome variables  \\\n",
       "22                                 Abortion attitudes   \n",
       "50                                     Vote for Trump   \n",
       "52                                     Vote for Trump   \n",
       "53  \"Gun ownership, rationales for owning firearms...   \n",
       "55                          Vote for Trump and Romney   \n",
       "61  Attitudes towards real female or male candidat...   \n",
       "68                 Attitudes toward sexual minorities   \n",
       "82  Ambivalent attitudes toward candidates (Trump ...   \n",
       "\n",
       "                                      Sexism concepts  \\\n",
       "22                     Hostile sexism (called Sexism)   \n",
       "50                                             Sexism   \n",
       "52                                             Sexism   \n",
       "53  Sexism, including items from modern sexism, ho...   \n",
       "55              Sexism\\nHostile sexism\\nModern sexism   \n",
       "61                                             Sexism   \n",
       "68                                             Sexism   \n",
       "82                                             Sexism   \n",
       "\n",
       "                                         Sexism items  \\\n",
       "22  \"Many women interpret innocent remarks or acts...   \n",
       "50  In Appendix E, not found online.\\n\\n\"We produc...   \n",
       "52  CCES\\n1) _x0007_Women should earn the same wag...   \n",
       "53  Recently there has been a lot of talk about wo...   \n",
       "55  1. Media should pay less attention to discrimi...   \n",
       "61  \"Women should return to their traditional role...   \n",
       "68  (1) Many women interpret innocent remarks or a...   \n",
       "82  ANES 1992-2000:\\ncloser to the equal role (1) ...   \n",
       "\n",
       "                                        Main findings  \\\n",
       "22  \"the indirect effect of sexism was smaller tha...   \n",
       "50  \"The effects of racial resentment and sexism w...   \n",
       "52  a \"profile—an amalgamation of attitudes about,...   \n",
       "53  \"relationship between sexism and gun ownership...   \n",
       "55  \"Sexist orientations had a greater impact on h...   \n",
       "61  Sexism is a negative predictor of favorability...   \n",
       "68  \"Individuals with a stronger adherence to sexi...   \n",
       "82  attitudinal ambivalence toward female candidat...   \n",
       "\n",
       "      Theoretical mechanism linking sexism to outcome Ambivalent sexism  \\\n",
       "22  From the Social Identity Theory (Tajfel & Turn...               NaN   \n",
       "50                                                NaN               NaN   \n",
       "52                                                NaN               NaN   \n",
       "53  Via gender ideologies, masculinist ideologies,...               NaN   \n",
       "55                                                NaN               NaN   \n",
       "61                                                NaN               NaN   \n",
       "68  People with sexist beliefs can have more negat...               NaN   \n",
       "82  \"Individuals who hold sexist attitudes should ...               NaN   \n",
       "\n",
       "   Benevolent sexism Hostile sexism Modern sexism Neosexism  \\\n",
       "22               NaN        Hostile           NaN       NaN   \n",
       "50               NaN            NaN           NaN       NaN   \n",
       "52               NaN            NaN           NaN       NaN   \n",
       "53               NaN        Hostile        Modern       NaN   \n",
       "55               NaN        Hostile        Modern       NaN   \n",
       "61               NaN            NaN           NaN       NaN   \n",
       "68               NaN            NaN           NaN       NaN   \n",
       "82               NaN            NaN           NaN       NaN   \n",
       "\n",
       "                                          concept_low  \n",
       "22                     hostile sexism (called sexism)  \n",
       "50                                             sexism  \n",
       "52                                             sexism  \n",
       "53  sexism, including items from modern sexism, ho...  \n",
       "55              sexism\\nhostile sexism\\nmodern sexism  \n",
       "61                                             sexism  \n",
       "68                                             sexism  \n",
       "82                                             sexism  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['Sexism concepts'].str.contains('Sexism'))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9237c273",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of papers using ANES data: 26\n",
      "Number of papers using CCES data: 12\n",
      "Number of papers using original data: 57\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['ANES',\n",
       " 'ANES (and CCES 2018-2020 in Appendix)',\n",
       " 'ANES 2016 and CCES 2018',\n",
       " 'ANES and Gun Survey',\n",
       " 'ANES and original survey (N = 1060)',\n",
       " 'ANES and original survey (N = 1400)',\n",
       " 'ANES and original survey (N = 716)',\n",
       " 'ANES, CCES',\n",
       " 'ANES, CCES, and original survey (N = 1100)',\n",
       " 'Australian Election Study',\n",
       " 'Australian Election Study and US Cooperative Congressional Study',\n",
       " 'Blair Center Poll',\n",
       " 'CCES',\n",
       " 'CCES and YouGov',\n",
       " 'CCES and an original survey (N = 1269)',\n",
       " 'CCES and original survey (N=1005, MTurk)',\n",
       " 'Canadian Election Studies (CES)',\n",
       " 'European Social Survey',\n",
       " 'National panel survey (NZAVS) and original survey (N = 309 students)',\n",
       " 'National survey',\n",
       " 'National survey (Cooperative Campaign Analysis Project)',\n",
       " 'National survey (NZAVS)',\n",
       " 'National survey (YouGov)',\n",
       " 'National survey and exit poll',\n",
       " 'Original Survey (N = 249, recruited via Facebook ads, among others; \"predominantly at men living in Utah between the ages of 18 and 45\")',\n",
       " 'Original national panel survey',\n",
       " 'Original national survey (N = 1077)',\n",
       " 'Original national survey (N = 1103)',\n",
       " 'Original national survey (N = 1197)',\n",
       " 'Original national survey (N = 1500 Catalan citizens)',\n",
       " 'Original national survey (N = 1501)',\n",
       " 'Original national survey (N = 1802)',\n",
       " 'Original national survey (N = 2290)',\n",
       " 'Original national survey (N = 3773)',\n",
       " 'Original national survey (N = 745)',\n",
       " 'Original survey (96 students)',\n",
       " 'Original survey (N = 1002)',\n",
       " 'Original survey (N = 1011)',\n",
       " 'Original survey (N = 106 students)',\n",
       " 'Original survey (N = 158)',\n",
       " 'Original survey (N = 239 undergraduates from a Southwestern university)',\n",
       " 'Original survey (N = 242)',\n",
       " 'Original survey (N = 244 students)',\n",
       " 'Original survey (N = 294 students)',\n",
       " 'Original survey (N = 303)',\n",
       " 'Original survey (N = 313, MTurk)',\n",
       " 'Original survey (N = 314 White women, Mturk)',\n",
       " 'Original survey (N = 447 students)',\n",
       " 'Original survey (N = 529)',\n",
       " 'Original survey (N = 578, Mturk)',\n",
       " 'Original survey (N = 781)',\n",
       " 'Original survey (N = 832)',\n",
       " 'Original survey (N = 875)',\n",
       " 'Original survey (N=1106, MTurk)',\n",
       " 'Original survey (N=1606, students and MTurk)',\n",
       " 'Original survey (N=1925 student-athletes)',\n",
       " 'Original survey (N=2806, MTurk)',\n",
       " 'Original survey (N=389 self-selected women)',\n",
       " 'Original survey (N=411 students)',\n",
       " 'Original survey (N=489, MTurk)',\n",
       " 'Original survey (N=743 voters)',\n",
       " 'Original survey (among self-identified Democrats, N = 1286)',\n",
       " 'Original survey among right-wing voters (N = 3718)',\n",
       " 'Original survey in a small Midwestern US city (N between 41 and 155)',\n",
       " 'Original surveys (N = 311 and N = 1099)',\n",
       " 'Six preexisting surveys (including ANES)',\n",
       " 'Three original surveys (N = 309, N = 2358, N = 2004)',\n",
       " 'Three original surveys (N = 550, N = 1192, N = 1074)',\n",
       " 'Two original surveys (N = 1120, Mturk, N = 2266)',\n",
       " 'Two original surveys (N = 202, N = 229)',\n",
       " 'Two original surveys (N = 327 in Thailand and N = 321 in Poland)',\n",
       " 'Two original surveys (N = 336 and N = 170 students)',\n",
       " 'Two original surveys (N = 474 and N = 242)',\n",
       " 'Two original surveys (N = 57 students and N = 189)',\n",
       " 'Two original surveys (N = 957, N = 409, Mturk)',\n",
       " 'VOTER survey']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examples of how to search through the data sets and items.\n",
    "\n",
    "c = 'Data sets'\n",
    "list(df[(df[c].str.contains('CCES'))]['Sexism items'])\n",
    "\n",
    "print(\"Number of papers using ANES data:\", df[c].str.contains('ANES').sum())\n",
    "print(\"Number of papers using CCES data:\", df[c].str.contains('CCES').sum())\n",
    "print(\"Number of papers using original data:\", df[c].str.contains('riginal').sum())\n",
    "sorted(df[c].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bf80b911",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "american journal of political science               1\n",
       "american politics research                          1\n",
       "analyses of social issues and public policy         8\n",
       "australian journal of political science             1\n",
       "behavioral sciences                                 1\n",
       "british journal of political science                2\n",
       "climatic change                                     1\n",
       "electoral studies                                   1\n",
       "ethnic and racial studies                           1\n",
       "forum                                               3\n",
       "french politics                                     1\n",
       "frontiers in political science                      4\n",
       "group processes and intergroup relations            3\n",
       "interdisciplinaria                                  1\n",
       "international journal of political economy          1\n",
       "journal of applied social psychology                1\n",
       "journal of elections, public opinion and parties    1\n",
       "journal of glbt family studies                      1\n",
       "journal of homosexuality                            1\n",
       "journal of personality and social psychology        1\n",
       "journal of race, ethnicity and politics             3\n",
       "journal of social psychology                        1\n",
       "journal of women, politics and policy               4\n",
       "personality and individual differences              3\n",
       "personality and social psychology bulletin          1\n",
       "personality assessment: new research                1\n",
       "plos one                                            1\n",
       "political analysis                                  1\n",
       "political behavior                                  4\n",
       "political psychology                                3\n",
       "political research quarterly                        3\n",
       "political science quarterly                         1\n",
       "politics and gender                                 9\n",
       "politics and religion                               1\n",
       "politics groups and identities                      4\n",
       "ps - political science and politics                 1\n",
       "psychology and sexuality                            1\n",
       "psychology of women quarterly                       1\n",
       "public opinion quarterly                            4\n",
       "representation                                      1\n",
       "research and politics                               1\n",
       "sex roles                                           7\n",
       "social psychology and society                       1\n",
       "social science quarterly                            4\n",
       "sociological inquiry                                1\n",
       "Name: Journal, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = 'Journal'\n",
    "df[c].str.lower().value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "338c8c95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of papers including Trump or Clinton in outcome variables: 40\n",
      "Number of papers including Trump in outcome variables: 36\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of papers including Trump or Clinton in outcome variables:\",(df['Outcome variables'].str.contains('Trump') | df['Outcome variables'].str.contains('Clinton')).sum())\n",
    "print(\"Number of papers including Trump in outcome variables:\",df['Outcome variables'].str.contains('Trump').sum())\n",
    "# print(\"List of papers including Clinton, but not Trump in outcome variables:\")\n",
    "# df[(~df['Outcome variables'].str.contains('Trump')) & df['Outcome variables'].str.contains('Clinton')]\n",
    "# df[(~df['Outcome variables'].str.contains('Trump')) & (~df['Outcome variables'].str.contains('Clinton')) & (df['Countries under study']=='USA')]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f159db8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of papers on presidential or primary elections: 47\n",
      "Number of papers on presidential or primary elections, not including Trump or Clinton: 10\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Author</th>\n",
       "      <th>Title</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Countries under study</th>\n",
       "      <th>Elections (if any)</th>\n",
       "      <th>Time under study</th>\n",
       "      <th>Data sets</th>\n",
       "      <th>Outcome variables</th>\n",
       "      <th>Sexism concepts</th>\n",
       "      <th>Sexism items</th>\n",
       "      <th>Main findings</th>\n",
       "      <th>Theoretical mechanism linking sexism to outcome</th>\n",
       "      <th>Ambivalent sexism</th>\n",
       "      <th>Benevolent sexism</th>\n",
       "      <th>Hostile sexism</th>\n",
       "      <th>Modern sexism</th>\n",
       "      <th>Neosexism</th>\n",
       "      <th>concept_low</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>Dwyer, Caitlin E.; Stevens, Daniel; Sullivan, ...</td>\n",
       "      <td>Racism, Sexism, and Candidate Evaluations in t...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2008</td>\n",
       "      <td>Original survey (N = 781)</td>\n",
       "      <td>Support for Obama and Palin</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"1) whether they believe that women miss out o...</td>\n",
       "      <td>\"Sexism […] did not significantly influence ev...</td>\n",
       "      <td>\"it is possible that Palin’s and Obama’s prese...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2011</td>\n",
       "      <td>Gervais, Sarah J.; Hillard, Amy L.</td>\n",
       "      <td>A role congruity perspective on prejudice towa...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential, parliamentary, regional (governor)</td>\n",
       "      <td>2008</td>\n",
       "      <td>Original survey (N = 244 students)</td>\n",
       "      <td>\"Evaluations of stereotypicality, competence, ...</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full Ambivalent Sexism Inventory (Glick and Fi...</td>\n",
       "      <td>\"participant gender, benevolent sexism, hostil...</td>\n",
       "      <td>Role congruity theory:\\n\"role congruity theory...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>Tate, Charlotte Chuck</td>\n",
       "      <td>Resentment of paternalism as system change sen...</td>\n",
       "      <td>Journal of Social Psychology</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2008</td>\n",
       "      <td>Original survey (96 students)</td>\n",
       "      <td>Vote for Obama/Biden or McCain/Palin</td>\n",
       "      <td>Benevolent sexism \\nHostile sexism \\nBenevolen...</td>\n",
       "      <td>Full Ambivalent Sexism Inventory (Glick and Fi...</td>\n",
       "      <td>\"The finding that greater resentment of patern...</td>\n",
       "      <td>\"removing the benevolence toward men construct...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism \\nhostile sexism \\nbenevolen...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016</td>\n",
       "      <td>McThomas, Mary; Tesler, Michael</td>\n",
       "      <td>The Growing Influence of Gender Attitudes on P...</td>\n",
       "      <td>Politics and Gender</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012</td>\n",
       "      <td>ANES, CCES</td>\n",
       "      <td>Favorability toward Clinton</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>ANES 2012:\\n\"How serious a problem is discrimi...</td>\n",
       "      <td>\"mass assessments of Hillary Clinton were shap...</td>\n",
       "      <td>\"Modern sexists, who believe women are receivi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2017</td>\n",
       "      <td>Blair, Karen L.</td>\n",
       "      <td>Did Secretary Clinton lose to a ‘basket of dep...</td>\n",
       "      <td>Psychology and Sexuality</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016 (data collected 2014-2015)</td>\n",
       "      <td>Original Survey (N = 249, recruited via Facebo...</td>\n",
       "      <td>Vote for Clinton, Trump and other candidates</td>\n",
       "      <td>Ambivalent sexism\\nBenevolent sexism\\nHostile ...</td>\n",
       "      <td>Full Ambivalent Sexism Inventory (Glick and Fi...</td>\n",
       "      <td>\"Ambivalent sexism was the strongest predictor...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ambivalent</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ambivalent sexism\\nbenevolent sexism\\nhostile ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2017</td>\n",
       "      <td>Bock, Jarrod; Byrd-Craven, Jennifer; Burkley, ...</td>\n",
       "      <td>The role of sexism in voting in the 2016 presi...</td>\n",
       "      <td>Personality and Individual Differences</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N = 239 undergraduates from a...</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full Ambivalent Sexism Inventory (Glick and Fi...</td>\n",
       "      <td>\"After controlling for participant sex, time o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2017</td>\n",
       "      <td>Simas, Elizabeth N.; Bumgardner, Marcia</td>\n",
       "      <td>Modern Sexism and the 2012 U.S. Presidential E...</td>\n",
       "      <td>Politics and Gender</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Romney (and Obama)</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>Denial of gender discrimination:\\n\"How serious...</td>\n",
       "      <td>\"a denial of gender discrimination problems cr...</td>\n",
       "      <td>Expect stronger effects among men because:\\n1)...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018</td>\n",
       "      <td>Frasure-Yokley, Lorrie</td>\n",
       "      <td>Choosing the velvet glove: Women voters, ambiv...</td>\n",
       "      <td>Journal of Race, Ethnicity and Politics</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Hostile sexism</td>\n",
       "      <td>\"Women fail to appreciate what men do for them...</td>\n",
       "      <td>\"Among white women, ambivalent sexist views po...</td>\n",
       "      <td>system justifying ideologies:\\n\"interdependenc...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018</td>\n",
       "      <td>Lytle, Ashley; Macdonald, Jamie; Dyar, Christi...</td>\n",
       "      <td>Ageism and Sexism in the 2016 United States Pr...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N = 875)</td>\n",
       "      <td>Attitudes toward Clinton and Trump (presidenti...</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"Discrimination against women is no longer a p...</td>\n",
       "      <td>\"Individuals who perceived sexism to be more p...</td>\n",
       "      <td>\"female politicians are judged based on gender...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2018</td>\n",
       "      <td>Pahlke, Erin; Bigler, Rebecca S.; Patterson, M...</td>\n",
       "      <td>Gender-Related Attitudes and Beliefs Predict W...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N = 314 White women, Mturk)</td>\n",
       "      <td>Vote and favorability for Clinton and Trump</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"1. Discrimination against women is no longer ...</td>\n",
       "      <td>\"Results indicated that women’s gender-related...</td>\n",
       "      <td>\"Women who perceive discrimination as a pervas...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018</td>\n",
       "      <td>Schaffner, Brian F.; Macwilliams, Matthew C.; ...</td>\n",
       "      <td>Understanding white polarization in the 2016 v...</td>\n",
       "      <td>Political Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>CCES and YouGov</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Hostile sexism</td>\n",
       "      <td>\"1. Women are too easily offended.\\n2. Many wo...</td>\n",
       "      <td>\"racial attitudes and sexism were much more st...</td>\n",
       "      <td>Explicit focus in Trump's rhetoric on race and...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018</td>\n",
       "      <td>Setzler, Mark; Yanus, Alixandra B.</td>\n",
       "      <td>Why Did Women Vote for Donald Trump?</td>\n",
       "      <td>PS - Political Science and Politics</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>1) \"How much discrimination is there in the Un...</td>\n",
       "      <td>\"although party affiliation was an important p...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018</td>\n",
       "      <td>Valentino, Nicholas A.; Wayne, Carly; Oceno, M...</td>\n",
       "      <td>Mobilizing sexism the interaction of emotion a...</td>\n",
       "      <td>Public Opinion Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2004-2016</td>\n",
       "      <td>ANES and original survey (N = 716)</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Hostile sexism\\nModern sexism</td>\n",
       "      <td>Hostile sexism:\\n1) Many women are actually se...</td>\n",
       "      <td>\"2016 was the only year in which [sexism] play...</td>\n",
       "      <td>\"an outwardly feminist, female candidate was r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2019</td>\n",
       "      <td>Barnello, Michelle A.; Bitecofer, Rachel; Kidd...</td>\n",
       "      <td>Ready for Hillary?: Explicit and Implicit Sexi...</td>\n",
       "      <td>Forum</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N=743 voters)</td>\n",
       "      <td>Vote for Clinton</td>\n",
       "      <td>Explicit sexism\\nImplicit sexism</td>\n",
       "      <td>Explicit (Yes or No):\\n\"America is ready for a...</td>\n",
       "      <td>\"The analysis reveals that even after controll...</td>\n",
       "      <td>\"The prospect of a woman serving as president ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>explicit sexism\\nimplicit sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2019</td>\n",
       "      <td>Bracic, Ana; Israel-Trummel, Mackenzie; Shortl...</td>\n",
       "      <td>Is Sexism for White People? Gender Stereotypes...</td>\n",
       "      <td>Political Behavior</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>National survey and exit poll</td>\n",
       "      <td>Vote and favorability for Trump</td>\n",
       "      <td>Politically defined\\nDomestically defined</td>\n",
       "      <td>Political: \"Do you agree or disagree with the ...</td>\n",
       "      <td>\"politically defined […] sexism […] predicts s...</td>\n",
       "      <td>\"We argue that the 2016 election implicated ge...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>politically defined\\ndomestically defined</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2019</td>\n",
       "      <td>Cassese, Erin C.; Barnes, Tiffany D.</td>\n",
       "      <td>Reconciling Sexism and Women’s Support for Rep...</td>\n",
       "      <td>Political Behavior</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012 and 2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Romney and Trump</td>\n",
       "      <td>Hostile sexism\\nModern sexism</td>\n",
       "      <td>Hostile sexism:\\n1) Do women demanding equalit...</td>\n",
       "      <td>\"white women endorse sexist beliefs, and that ...</td>\n",
       "      <td>Intersectionality and system justification:\\n\"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2019</td>\n",
       "      <td>Cassese, Erin C.; Holman, Mirya R.</td>\n",
       "      <td>Playing the Woman Card: Ambivalent Sexism in t...</td>\n",
       "      <td>Political Psychology</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Two original surveys (N = 957, N = 409, Mturk)</td>\n",
       "      <td>Vote for Clinton and Trump\\nEvaluations of Cli...</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full Ambivalent Sexism Scale (Glick and Fiske ...</td>\n",
       "      <td>\"hostile sexists exposed to the [Trump’s \"woma...</td>\n",
       "      <td>System justification theory:\\n\"Trump’s attacks...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2019</td>\n",
       "      <td>Cassidy, Brittany S.; Krendl, Anne C.</td>\n",
       "      <td>A Crisis of Competence: Benevolent Sexism Affe...</td>\n",
       "      <td>Sex Roles</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Two original surveys (N = 57 students and N = ...</td>\n",
       "      <td>Perceived competence of Clinton and Trump\\nAtt...</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full Ambivalent Sexism Scale (Glick and Fiske ...</td>\n",
       "      <td>\"benevolent (and not hostile) sexism predicted...</td>\n",
       "      <td>\"Reflecting shifting standards (a tendency to ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2019</td>\n",
       "      <td>Glick, Peter</td>\n",
       "      <td>Gender, sexism, and the election: did sexism h...</td>\n",
       "      <td>Politics Groups and Identities</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>National survey</td>\n",
       "      <td>Favorability toward Clinton and Trump</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Hostile:\\nWomen seek to gain power by getting ...</td>\n",
       "      <td>\"Hostile sexist attitudes were second only to ...</td>\n",
       "      <td>Sexism stems from male dominance, so both host...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2019</td>\n",
       "      <td>Godbole, Maya A.; Malvar, Noelle A.; Valian, V...</td>\n",
       "      <td>Gender, Modern Sexism, and the 2016 election</td>\n",
       "      <td>Politics Groups and Identities</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original surveys (N = 311 and N = 1099)</td>\n",
       "      <td>Favorability toward Clinton and Trump</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>Full Modern Sexism Scale (Swim et al. 1995), 8...</td>\n",
       "      <td>\"Although Clinton matched the ideal better tha...</td>\n",
       "      <td>\"Modern Sexism might exacerbate demands to fit...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2019</td>\n",
       "      <td>Knuckey, Jonathan</td>\n",
       "      <td>\"I Just Don't Think She Has a Presidential Loo...</td>\n",
       "      <td>Social Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Modern sexism\\nTraditional sexism</td>\n",
       "      <td>Modern sexism:\\n\"(1) how much attention the me...</td>\n",
       "      <td>\"Both modern and traditional sexism were signi...</td>\n",
       "      <td>\"the mere presence of a woman running for the ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism\\ntraditional sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2019</td>\n",
       "      <td>Ratliff, Kate A.; Redford, Liz; Conway, John; ...</td>\n",
       "      <td>Engendering support: Hostile sexism predicts v...</td>\n",
       "      <td>Group Processes and Intergroup Relations</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Three original surveys (N = 550, N = 1192, N =...</td>\n",
       "      <td>Attitudes toward Clinton and Trump\\nVote for T...</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Study 1:\\nSix items on hostile sexism\\nSix ite...</td>\n",
       "      <td>\"greater hostile sexism predicted more positiv...</td>\n",
       "      <td>Hostile sexists dislike women who break the st...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2019</td>\n",
       "      <td>Rothwell, Valerie; Hodson, Gordon; Prusaczyk, ...</td>\n",
       "      <td>Why Pillory Hillary? Testing the endemic sexis...</td>\n",
       "      <td>Personality and Individual Differences</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Hostile sexism</td>\n",
       "      <td>(1) \"many women interpret innocent remarks as ...</td>\n",
       "      <td>\"Greater conservatism or sexism significantly ...</td>\n",
       "      <td>\"if sexism influenced voters' decisions, left-...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2020</td>\n",
       "      <td>Ferguson, Thomas; Page, Benjamin I.; Rothschil...</td>\n",
       "      <td>The Roots of Right-Wing Populism: Donald Trump...</td>\n",
       "      <td>International Journal of Political Economy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and Republican primaries</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"modern sexism scale, and feelings about the A...</td>\n",
       "      <td>Sexism did not predict vote for Trump in the p...</td>\n",
       "      <td>\"More important is the fact that there was lit...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2020</td>\n",
       "      <td>Monteith, Margo J.; Hildebrand, Laura K.</td>\n",
       "      <td>Sexism, perceived discrimination, and system j...</td>\n",
       "      <td>Group Processes and Intergroup Relations</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N=1606, students and MTurk)</td>\n",
       "      <td>Candidate preference (Trump vs. Clinton)</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism\\nModern sexism</td>\n",
       "      <td>Full ASI scale (Glick and Fiske 1996)\\nFull mo...</td>\n",
       "      <td>\"Controlling for conservatism, we found that (...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2020</td>\n",
       "      <td>Shook, Natalie J.; Fitzgerald, Holly N.; Boggs...</td>\n",
       "      <td>Sexism, racism, and nationalism: Factors assoc...</td>\n",
       "      <td>PLoS ONE</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N=489, MTurk)</td>\n",
       "      <td>Vote for and evaluation of Trump and Clinton</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full ASI scale (Glick and Fiske 1996)</td>\n",
       "      <td>\"Sexism toward women and U.S. nationalism were...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2021</td>\n",
       "      <td>Buyuker, Beyza; Durso, Amanda Jadidi; Filindra...</td>\n",
       "      <td>Race politics research and the American presid...</td>\n",
       "      <td>Journal of Race, Ethnicity and Politics</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and Republican primary</td>\n",
       "      <td>2016-2020</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>In Appendix E, not found online.\\n\\n\"We produc...</td>\n",
       "      <td>\"The effects of racial resentment and sexism w...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2021</td>\n",
       "      <td>Enders, Adam M.; Uscinski, Joseph E.</td>\n",
       "      <td>On Modeling the Social-Psychological Foundatio...</td>\n",
       "      <td>American Politics Research</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES 2016 and CCES 2018</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>CCES\\n1) _x0007_Women should earn the same wag...</td>\n",
       "      <td>a \"profile—an amalgamation of attitudes about,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2021</td>\n",
       "      <td>Franks, Andrew S.</td>\n",
       "      <td>The Conditional Effects of Candidate Sex and S...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Democratic primary and Presidential</td>\n",
       "      <td>2019-2020</td>\n",
       "      <td>Two original surveys (N = 202, N = 229)</td>\n",
       "      <td>Vote for six Democratic candidates (including ...</td>\n",
       "      <td>Hostile sexism</td>\n",
       "      <td>4 items from ANES, i.e.:\\n\"(1) \"many women int...</td>\n",
       "      <td>\"Study 1 found deleterious effects of hostile ...</td>\n",
       "      <td>\"Voters may hold male and female candidates to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2021</td>\n",
       "      <td>Hanley, Eric</td>\n",
       "      <td>Sexism as a political force: The impact of gen...</td>\n",
       "      <td>Social Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012 and 2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Vote for Trump and Romney</td>\n",
       "      <td>Sexism\\nHostile sexism\\nModern sexism</td>\n",
       "      <td>1. Media should pay less attention to discrimi...</td>\n",
       "      <td>\"Sexist orientations had a greater impact on h...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism\\nhostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2021</td>\n",
       "      <td>Maxwell, Angie</td>\n",
       "      <td>Why Trump Became a `Confederate' President</td>\n",
       "      <td>Forum</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and Republican primary</td>\n",
       "      <td>2016-2020</td>\n",
       "      <td>Blair Center Poll</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"1. Many women are actually seeking special fa...</td>\n",
       "      <td>Modern sexism was a significant predictor of v...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2021</td>\n",
       "      <td>Medenica, Vladimir E.; Fowler, Matthew</td>\n",
       "      <td>Candidate Preference, State Context, and Voter...</td>\n",
       "      <td>Forum</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Preference for Trump and Clinton (among non-vo...</td>\n",
       "      <td>Ambivalent sexism</td>\n",
       "      <td>\"1. ‘Many women interpret innocent remarks or ...</td>\n",
       "      <td>Ambivalent sexism coefficient is not statistic...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ambivalent</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ambivalent sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2021</td>\n",
       "      <td>Nelson, Kjersten</td>\n",
       "      <td>You seem like a great candidate, but... : race...</td>\n",
       "      <td>Journal of Race, Ethnicity and Politics</td>\n",
       "      <td>USA</td>\n",
       "      <td>Democratic primary</td>\n",
       "      <td>2019</td>\n",
       "      <td>Original survey (among self-identified Democra...</td>\n",
       "      <td>Candidate evaluation (including Biden, Harris,...</td>\n",
       "      <td>Hostile sexism\\nModern sexism</td>\n",
       "      <td>6 hostile sexism items \"reflects ANES\"\\n1 mode...</td>\n",
       "      <td>\"Using a survey of self-identified Democrats, ...</td>\n",
       "      <td>\"heuristic search\"\\n\"Campaigns’ emphases on ge...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2021</td>\n",
       "      <td>Spencer, Bettina</td>\n",
       "      <td>Impact of racism and sexism in the 2008–2020 U...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2008, 2012, 2016, 2020</td>\n",
       "      <td>Original survey in a small Midwestern US city ...</td>\n",
       "      <td>Vote for presidential candidates (including Ob...</td>\n",
       "      <td>Benevolent sexism\\nHostile sexism</td>\n",
       "      <td>Full ASI scale (Glick and Fiske 2001)</td>\n",
       "      <td>\"Although benevolent sexism was a significant ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>benevolent sexism\\nhostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2021</td>\n",
       "      <td>Utych, Stephen M.</td>\n",
       "      <td>Sexism predicts favorability of women in the 2...</td>\n",
       "      <td>Electoral Studies</td>\n",
       "      <td>USA</td>\n",
       "      <td>Democratic primary</td>\n",
       "      <td>2019</td>\n",
       "      <td>VOTER survey</td>\n",
       "      <td>Attitudes towards real female or male candidat...</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>\"Women should return to their traditional role...</td>\n",
       "      <td>Sexism is a negative predictor of favorability...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2022</td>\n",
       "      <td>Banda, Kevin K.; Cassese, Erin C.</td>\n",
       "      <td>Hostile Sexism, Racial Resentment, and Politic...</td>\n",
       "      <td>Political Behavior</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and parliamentary</td>\n",
       "      <td>2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Voter turnout\\nEngagement with political campa...</td>\n",
       "      <td>Hostile sexism</td>\n",
       "      <td>(1) \"many women interpret innocent remarks as ...</td>\n",
       "      <td>Hostile sexism proved demobilizing for Democra...</td>\n",
       "      <td>\"For Democrats, high levels of hostile sexism ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2022</td>\n",
       "      <td>Calvert, Gemma Anne; Evans, Geoffrey; Pathak, ...</td>\n",
       "      <td>Race, Gender, and the U.S. Presidency: A Compa...</td>\n",
       "      <td>Behavioral Sciences</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2012 (asked 2014-2015)</td>\n",
       "      <td>Original national survey (N = 1077)</td>\n",
       "      <td>Voting for Romney or Obama</td>\n",
       "      <td>Neosexism\\nImplicit bias</td>\n",
       "      <td>Implicit: evaluative priming paradigm\\n\\nExpli...</td>\n",
       "      <td>\"we observed that measures of implicit bias ar...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Neosexism</td>\n",
       "      <td>neosexism\\nimplicit bias</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2022</td>\n",
       "      <td>Filindra, Alexandra; Fagan, E.J.</td>\n",
       "      <td>Black, immigrant, or woman? The implicit influ...</td>\n",
       "      <td>Social Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2020</td>\n",
       "      <td>Original survey (N = 832)</td>\n",
       "      <td>Vote for Biden</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"Difference between perceptions of discriminat...</td>\n",
       "      <td>\"we find that respondents with moderate levels...</td>\n",
       "      <td>\"mention of Harris will make gender priors sal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2022</td>\n",
       "      <td>Godbole, Maya A.; Flores-Robles, Grace; Malvar...</td>\n",
       "      <td>Who do you like? Who will you vote for? Politi...</td>\n",
       "      <td>Analyses of Social Issues and Public Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2020</td>\n",
       "      <td>Original survey (N = 578, Mturk)</td>\n",
       "      <td>Evaluations of Biden and Trump (competence, mo...</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"eight items that measured denial of continuin...</td>\n",
       "      <td>Modern sexism predicted favorability toward Tr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2022</td>\n",
       "      <td>Hayes, Danny; Lawless, Jennifer L.</td>\n",
       "      <td>The Contingent Effects of Sexism in Primary El...</td>\n",
       "      <td>Political Research Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>State legislative primary (abstract)</td>\n",
       "      <td>2016 and 2018</td>\n",
       "      <td>Two original surveys (N = 1120, Mturk, N = 2266)</td>\n",
       "      <td>Vote for a fictitious female candidate in stat...</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"(1) how much discrimination they believe wome...</td>\n",
       "      <td>\"when a male candidate attempts to activate se...</td>\n",
       "      <td>Standard political communication framework: \"a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2022</td>\n",
       "      <td>Hickel, Flavio R., Jr.; Murphy, Andrew R.</td>\n",
       "      <td>Making America Exceptional Again: Donald Trump...</td>\n",
       "      <td>Politics and Religion</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>CCES</td>\n",
       "      <td>Mid-term approval for Trump\\nEmotional affect ...</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>\"Resentment of feminism\"\\n(1) \"When women lose...</td>\n",
       "      <td>\"adherence to the tenets of American civil rel...</td>\n",
       "      <td>\"we contend that the confluence of civil relig...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2022</td>\n",
       "      <td>Hickel, Flavio Rogerio; Deckman, Melissa</td>\n",
       "      <td>Did sexism drive Latino support for Trump? Lat...</td>\n",
       "      <td>Social Science Quarterly</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016 and 2020</td>\n",
       "      <td>ANES (and CCES 2018-2020 in Appendix)</td>\n",
       "      <td>Vote for Trump</td>\n",
       "      <td>Modern sexism\\nTraditional sexism</td>\n",
       "      <td>Modern sexism:\\n\"1. When women demand equality...</td>\n",
       "      <td>\"While Latinxs do express higher levels of sex...</td>\n",
       "      <td>\"Absent meaningful conceptual differences betw...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism\\ntraditional sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2022</td>\n",
       "      <td>Long, Meri T.; Dawe, Ryan; Suhay, Elizabeth</td>\n",
       "      <td>Gender Attitudes and Candidate Preferences in ...</td>\n",
       "      <td>Politics and Gender</td>\n",
       "      <td>USA</td>\n",
       "      <td>Democratic primary and Presidential</td>\n",
       "      <td>2016</td>\n",
       "      <td>Original survey (N = 1002)</td>\n",
       "      <td>Feelings towards candidates (including Clinton...</td>\n",
       "      <td>Hostile sexism\\nModern sexism</td>\n",
       "      <td>\"Hostile Sexism\\nOnce a woman gets a man to co...</td>\n",
       "      <td>\"We find that among Democrats, hostile sexists...</td>\n",
       "      <td>\"citizens’ gender-relevant attitudes, in conju...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism\\nmodern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2023</td>\n",
       "      <td>Bauer, Nichole M.</td>\n",
       "      <td>Gendered Ambivalence: The Structure of Attitud...</td>\n",
       "      <td>Journal of Women, Politics and Policy</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and parliamentary</td>\n",
       "      <td>1992-2000 and 2016</td>\n",
       "      <td>ANES</td>\n",
       "      <td>Ambivalent attitudes toward candidates (Trump ...</td>\n",
       "      <td>Sexism</td>\n",
       "      <td>ANES 1992-2000:\\ncloser to the equal role (1) ...</td>\n",
       "      <td>attitudinal ambivalence toward female candidat...</td>\n",
       "      <td>\"Individuals who hold sexist attitudes should ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2023</td>\n",
       "      <td>Oceno, Marzia; Valentino, Nicholas A.; Wayne, ...</td>\n",
       "      <td>The Electoral Costs and Benefits of Feminism i...</td>\n",
       "      <td>Political Behavior</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential</td>\n",
       "      <td>2016 and 2018</td>\n",
       "      <td>ANES, CCES, and original survey (N = 1100)</td>\n",
       "      <td>Vote for Clinton</td>\n",
       "      <td>Modern sexism</td>\n",
       "      <td>Original SSI (items from ASI, but directly ref...</td>\n",
       "      <td>\"Concerns that women are trying to dominate me...</td>\n",
       "      <td>\"we expect sexism directed against feminists, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Modern</td>\n",
       "      <td>NaN</td>\n",
       "      <td>modern sexism</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>2023</td>\n",
       "      <td>Winter, Nicholas J. G.</td>\n",
       "      <td>Hostile Sexism, Benevolent Sexism, and America...</td>\n",
       "      <td>Politics and Gender</td>\n",
       "      <td>USA</td>\n",
       "      <td>Presidential and parliamentary</td>\n",
       "      <td>2016</td>\n",
       "      <td>CCES and an original survey (N = 1269)</td>\n",
       "      <td>Support for Trump/Clinton\\nSupport for real an...</td>\n",
       "      <td>Hostile sexism\\nBenevolent sexism</td>\n",
       "      <td>\"Benevolent Sexism\\n1. Many women have a quali...</td>\n",
       "      <td>Hostile and benevolent sexism increase support...</td>\n",
       "      <td>1) Hostile sexism is directed at women who see...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Benevolent</td>\n",
       "      <td>Hostile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>hostile sexism\\nbenevolent sexism</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year                                             Author  \\\n",
       "1   2009  Dwyer, Caitlin E.; Stevens, Daniel; Sullivan, ...   \n",
       "5   2011                 Gervais, Sarah J.; Hillard, Amy L.   \n",
       "10  2014                              Tate, Charlotte Chuck   \n",
       "12  2016                    McThomas, Mary; Tesler, Michael   \n",
       "14  2017                                    Blair, Karen L.   \n",
       "15  2017  Bock, Jarrod; Byrd-Craven, Jennifer; Burkley, ...   \n",
       "17  2017            Simas, Elizabeth N.; Bumgardner, Marcia   \n",
       "18  2018                             Frasure-Yokley, Lorrie   \n",
       "19  2018  Lytle, Ashley; Macdonald, Jamie; Dyar, Christi...   \n",
       "21  2018  Pahlke, Erin; Bigler, Rebecca S.; Patterson, M...   \n",
       "23  2018  Schaffner, Brian F.; Macwilliams, Matthew C.; ...   \n",
       "24  2018                 Setzler, Mark; Yanus, Alixandra B.   \n",
       "25  2018  Valentino, Nicholas A.; Wayne, Carly; Oceno, M...   \n",
       "26  2019  Barnello, Michelle A.; Bitecofer, Rachel; Kidd...   \n",
       "27  2019  Bracic, Ana; Israel-Trummel, Mackenzie; Shortl...   \n",
       "28  2019               Cassese, Erin C.; Barnes, Tiffany D.   \n",
       "29  2019                 Cassese, Erin C.; Holman, Mirya R.   \n",
       "30  2019              Cassidy, Brittany S.; Krendl, Anne C.   \n",
       "32  2019                                       Glick, Peter   \n",
       "33  2019  Godbole, Maya A.; Malvar, Noelle A.; Valian, V...   \n",
       "34  2019                                  Knuckey, Jonathan   \n",
       "36  2019  Ratliff, Kate A.; Redford, Liz; Conway, John; ...   \n",
       "37  2019  Rothwell, Valerie; Hodson, Gordon; Prusaczyk, ...   \n",
       "43  2020  Ferguson, Thomas; Page, Benjamin I.; Rothschil...   \n",
       "44  2020           Monteith, Margo J.; Hildebrand, Laura K.   \n",
       "45  2020  Shook, Natalie J.; Fitzgerald, Holly N.; Boggs...   \n",
       "50  2021  Buyuker, Beyza; Durso, Amanda Jadidi; Filindra...   \n",
       "52  2021               Enders, Adam M.; Uscinski, Joseph E.   \n",
       "54  2021                                  Franks, Andrew S.   \n",
       "55  2021                                       Hanley, Eric   \n",
       "57  2021                                     Maxwell, Angie   \n",
       "58  2021             Medenica, Vladimir E.; Fowler, Matthew   \n",
       "59  2021                                   Nelson, Kjersten   \n",
       "60  2021                                   Spencer, Bettina   \n",
       "61  2021                                  Utych, Stephen M.   \n",
       "66  2022                  Banda, Kevin K.; Cassese, Erin C.   \n",
       "69  2022  Calvert, Gemma Anne; Evans, Geoffrey; Pathak, ...   \n",
       "71  2022                   Filindra, Alexandra; Fagan, E.J.   \n",
       "72  2022  Godbole, Maya A.; Flores-Robles, Grace; Malvar...   \n",
       "74  2022                 Hayes, Danny; Lawless, Jennifer L.   \n",
       "75  2022          Hickel, Flavio R., Jr.; Murphy, Andrew R.   \n",
       "76  2022           Hickel, Flavio Rogerio; Deckman, Melissa   \n",
       "79  2022        Long, Meri T.; Dawe, Ryan; Suhay, Elizabeth   \n",
       "82  2023                                  Bauer, Nichole M.   \n",
       "90  2023  Oceno, Marzia; Valentino, Nicholas A.; Wayne, ...   \n",
       "94  2023                             Winter, Nicholas J. G.   \n",
       "\n",
       "                                                Title  \\\n",
       "1   Racism, Sexism, and Candidate Evaluations in t...   \n",
       "5   A role congruity perspective on prejudice towa...   \n",
       "10  Resentment of paternalism as system change sen...   \n",
       "12  The Growing Influence of Gender Attitudes on P...   \n",
       "14  Did Secretary Clinton lose to a ‘basket of dep...   \n",
       "15  The role of sexism in voting in the 2016 presi...   \n",
       "17  Modern Sexism and the 2012 U.S. Presidential E...   \n",
       "18  Choosing the velvet glove: Women voters, ambiv...   \n",
       "19  Ageism and Sexism in the 2016 United States Pr...   \n",
       "21  Gender-Related Attitudes and Beliefs Predict W...   \n",
       "23  Understanding white polarization in the 2016 v...   \n",
       "24               Why Did Women Vote for Donald Trump?   \n",
       "25  Mobilizing sexism the interaction of emotion a...   \n",
       "26  Ready for Hillary?: Explicit and Implicit Sexi...   \n",
       "27  Is Sexism for White People? Gender Stereotypes...   \n",
       "28  Reconciling Sexism and Women’s Support for Rep...   \n",
       "29  Playing the Woman Card: Ambivalent Sexism in t...   \n",
       "30  A Crisis of Competence: Benevolent Sexism Affe...   \n",
       "32  Gender, sexism, and the election: did sexism h...   \n",
       "33       Gender, Modern Sexism, and the 2016 election   \n",
       "34  \"I Just Don't Think She Has a Presidential Loo...   \n",
       "36  Engendering support: Hostile sexism predicts v...   \n",
       "37  Why Pillory Hillary? Testing the endemic sexis...   \n",
       "43  The Roots of Right-Wing Populism: Donald Trump...   \n",
       "44  Sexism, perceived discrimination, and system j...   \n",
       "45  Sexism, racism, and nationalism: Factors assoc...   \n",
       "50  Race politics research and the American presid...   \n",
       "52  On Modeling the Social-Psychological Foundatio...   \n",
       "54  The Conditional Effects of Candidate Sex and S...   \n",
       "55  Sexism as a political force: The impact of gen...   \n",
       "57         Why Trump Became a `Confederate' President   \n",
       "58  Candidate Preference, State Context, and Voter...   \n",
       "59  You seem like a great candidate, but... : race...   \n",
       "60  Impact of racism and sexism in the 2008–2020 U...   \n",
       "61  Sexism predicts favorability of women in the 2...   \n",
       "66  Hostile Sexism, Racial Resentment, and Politic...   \n",
       "69  Race, Gender, and the U.S. Presidency: A Compa...   \n",
       "71  Black, immigrant, or woman? The implicit influ...   \n",
       "72  Who do you like? Who will you vote for? Politi...   \n",
       "74  The Contingent Effects of Sexism in Primary El...   \n",
       "75  Making America Exceptional Again: Donald Trump...   \n",
       "76  Did sexism drive Latino support for Trump? Lat...   \n",
       "79  Gender Attitudes and Candidate Preferences in ...   \n",
       "82  Gendered Ambivalence: The Structure of Attitud...   \n",
       "90  The Electoral Costs and Benefits of Feminism i...   \n",
       "94  Hostile Sexism, Benevolent Sexism, and America...   \n",
       "\n",
       "                                        Journal Countries under study  \\\n",
       "1   Analyses of Social Issues and Public Policy                   USA   \n",
       "5   Analyses of Social Issues and Public Policy                   USA   \n",
       "10                 Journal of Social Psychology                   USA   \n",
       "12                          Politics and Gender                   USA   \n",
       "14                     Psychology and Sexuality                   USA   \n",
       "15       Personality and Individual Differences                   USA   \n",
       "17                          Politics and Gender                   USA   \n",
       "18      Journal of Race, Ethnicity and Politics                   USA   \n",
       "19  Analyses of Social Issues and Public Policy                   USA   \n",
       "21  Analyses of Social Issues and Public Policy                   USA   \n",
       "23                  Political Science Quarterly                   USA   \n",
       "24          PS - Political Science and Politics                   USA   \n",
       "25                     Public Opinion Quarterly                   USA   \n",
       "26                                        Forum                   USA   \n",
       "27                           Political Behavior                   USA   \n",
       "28                           Political Behavior                   USA   \n",
       "29                         Political Psychology                   USA   \n",
       "30                                    Sex Roles                   USA   \n",
       "32               Politics Groups and Identities                   USA   \n",
       "33               Politics Groups and Identities                   USA   \n",
       "34                     Social Science Quarterly                   USA   \n",
       "36     Group Processes and Intergroup Relations                   USA   \n",
       "37       Personality and Individual Differences                   USA   \n",
       "43   International Journal of Political Economy                   USA   \n",
       "44     Group Processes and Intergroup Relations                   USA   \n",
       "45                                     PLoS ONE                   USA   \n",
       "50      Journal of Race, Ethnicity and Politics                   USA   \n",
       "52                   American Politics Research                   USA   \n",
       "54  Analyses of Social Issues and Public Policy                   USA   \n",
       "55                     Social Science Quarterly                   USA   \n",
       "57                                        Forum                   USA   \n",
       "58                                        Forum                   USA   \n",
       "59      Journal of Race, Ethnicity and Politics                   USA   \n",
       "60  Analyses of Social Issues and Public Policy                   USA   \n",
       "61                            Electoral Studies                   USA   \n",
       "66                           Political Behavior                   USA   \n",
       "69                          Behavioral Sciences                   USA   \n",
       "71                     Social Science Quarterly                   USA   \n",
       "72  Analyses of Social Issues and Public Policy                   USA   \n",
       "74                 Political Research Quarterly                   USA   \n",
       "75                        Politics and Religion                   USA   \n",
       "76                     Social Science Quarterly                   USA   \n",
       "79                          Politics and Gender                   USA   \n",
       "82        Journal of Women, Politics and Policy                   USA   \n",
       "90                           Political Behavior                   USA   \n",
       "94                          Politics and Gender                   USA   \n",
       "\n",
       "                                  Elections (if any)  \\\n",
       "1                                       Presidential   \n",
       "5   Presidential, parliamentary, regional (governor)   \n",
       "10                                      Presidential   \n",
       "12                                      Presidential   \n",
       "14                                      Presidential   \n",
       "15                                      Presidential   \n",
       "17                                      Presidential   \n",
       "18                                      Presidential   \n",
       "19                                      Presidential   \n",
       "21                                      Presidential   \n",
       "23                                      Presidential   \n",
       "24                                      Presidential   \n",
       "25                                      Presidential   \n",
       "26                                      Presidential   \n",
       "27                                      Presidential   \n",
       "28                                      Presidential   \n",
       "29                                      Presidential   \n",
       "30                                      Presidential   \n",
       "32                                      Presidential   \n",
       "33                                      Presidential   \n",
       "34                                      Presidential   \n",
       "36                                      Presidential   \n",
       "37                                      Presidential   \n",
       "43             Presidential and Republican primaries   \n",
       "44                                      Presidential   \n",
       "45                                      Presidential   \n",
       "50               Presidential and Republican primary   \n",
       "52                                      Presidential   \n",
       "54               Democratic primary and Presidential   \n",
       "55                                      Presidential   \n",
       "57               Presidential and Republican primary   \n",
       "58                                      Presidential   \n",
       "59                                Democratic primary   \n",
       "60                                      Presidential   \n",
       "61                                Democratic primary   \n",
       "66                    Presidential and parliamentary   \n",
       "69                                      Presidential   \n",
       "71                                      Presidential   \n",
       "72                                      Presidential   \n",
       "74              State legislative primary (abstract)   \n",
       "75                                      Presidential   \n",
       "76                                      Presidential   \n",
       "79               Democratic primary and Presidential   \n",
       "82                    Presidential and parliamentary   \n",
       "90                                      Presidential   \n",
       "94                    Presidential and parliamentary   \n",
       "\n",
       "                   Time under study  \\\n",
       "1                              2008   \n",
       "5                              2008   \n",
       "10                             2008   \n",
       "12                             2012   \n",
       "14  2016 (data collected 2014-2015)   \n",
       "15                             2016   \n",
       "17                             2012   \n",
       "18                             2016   \n",
       "19                             2016   \n",
       "21                             2016   \n",
       "23                             2016   \n",
       "24                             2016   \n",
       "25                        2004-2016   \n",
       "26                             2016   \n",
       "27                             2016   \n",
       "28                    2012 and 2016   \n",
       "29                             2016   \n",
       "30                             2016   \n",
       "32                             2016   \n",
       "33                             2016   \n",
       "34                             2016   \n",
       "36                             2016   \n",
       "37                             2016   \n",
       "43                             2016   \n",
       "44                             2016   \n",
       "45                             2016   \n",
       "50                        2016-2020   \n",
       "52                             2016   \n",
       "54                        2019-2020   \n",
       "55                    2012 and 2016   \n",
       "57                        2016-2020   \n",
       "58                             2016   \n",
       "59                             2019   \n",
       "60           2008, 2012, 2016, 2020   \n",
       "61                             2019   \n",
       "66                             2016   \n",
       "69           2012 (asked 2014-2015)   \n",
       "71                             2020   \n",
       "72                             2020   \n",
       "74                    2016 and 2018   \n",
       "75                             2016   \n",
       "76                    2016 and 2020   \n",
       "79                             2016   \n",
       "82               1992-2000 and 2016   \n",
       "90                    2016 and 2018   \n",
       "94                             2016   \n",
       "\n",
       "                                            Data sets  \\\n",
       "1                           Original survey (N = 781)   \n",
       "5                  Original survey (N = 244 students)   \n",
       "10                      Original survey (96 students)   \n",
       "12                                         ANES, CCES   \n",
       "14  Original Survey (N = 249, recruited via Facebo...   \n",
       "15  Original survey (N = 239 undergraduates from a...   \n",
       "17                                               ANES   \n",
       "18                                               ANES   \n",
       "19                          Original survey (N = 875)   \n",
       "21       Original survey (N = 314 White women, Mturk)   \n",
       "23                                    CCES and YouGov   \n",
       "24                                               ANES   \n",
       "25                 ANES and original survey (N = 716)   \n",
       "26                     Original survey (N=743 voters)   \n",
       "27                      National survey and exit poll   \n",
       "28                                               ANES   \n",
       "29     Two original surveys (N = 957, N = 409, Mturk)   \n",
       "30  Two original surveys (N = 57 students and N = ...   \n",
       "32                                    National survey   \n",
       "33            Original surveys (N = 311 and N = 1099)   \n",
       "34                                               ANES   \n",
       "36  Three original surveys (N = 550, N = 1192, N =...   \n",
       "37                                               ANES   \n",
       "43                                               ANES   \n",
       "44       Original survey (N=1606, students and MTurk)   \n",
       "45                     Original survey (N=489, MTurk)   \n",
       "50                                               ANES   \n",
       "52                            ANES 2016 and CCES 2018   \n",
       "54            Two original surveys (N = 202, N = 229)   \n",
       "55                                               ANES   \n",
       "57                                  Blair Center Poll   \n",
       "58                                               ANES   \n",
       "59  Original survey (among self-identified Democra...   \n",
       "60  Original survey in a small Midwestern US city ...   \n",
       "61                                       VOTER survey   \n",
       "66                                               ANES   \n",
       "69                Original national survey (N = 1077)   \n",
       "71                          Original survey (N = 832)   \n",
       "72                   Original survey (N = 578, Mturk)   \n",
       "74   Two original surveys (N = 1120, Mturk, N = 2266)   \n",
       "75                                               CCES   \n",
       "76              ANES (and CCES 2018-2020 in Appendix)   \n",
       "79                         Original survey (N = 1002)   \n",
       "82                                               ANES   \n",
       "90         ANES, CCES, and original survey (N = 1100)   \n",
       "94             CCES and an original survey (N = 1269)   \n",
       "\n",
       "                                    Outcome variables  \\\n",
       "1                         Support for Obama and Palin   \n",
       "5   \"Evaluations of stereotypicality, competence, ...   \n",
       "10               Vote for Obama/Biden or McCain/Palin   \n",
       "12                        Favorability toward Clinton   \n",
       "14       Vote for Clinton, Trump and other candidates   \n",
       "15                                     Vote for Trump   \n",
       "17                        Vote for Romney (and Obama)   \n",
       "18                                     Vote for Trump   \n",
       "19  Attitudes toward Clinton and Trump (presidenti...   \n",
       "21        Vote and favorability for Clinton and Trump   \n",
       "23                                     Vote for Trump   \n",
       "24                                     Vote for Trump   \n",
       "25                                     Vote for Trump   \n",
       "26                                   Vote for Clinton   \n",
       "27                    Vote and favorability for Trump   \n",
       "28                          Vote for Romney and Trump   \n",
       "29  Vote for Clinton and Trump\\nEvaluations of Cli...   \n",
       "30  Perceived competence of Clinton and Trump\\nAtt...   \n",
       "32              Favorability toward Clinton and Trump   \n",
       "33              Favorability toward Clinton and Trump   \n",
       "34                                     Vote for Trump   \n",
       "36  Attitudes toward Clinton and Trump\\nVote for T...   \n",
       "37                                     Vote for Trump   \n",
       "43                                     Vote for Trump   \n",
       "44           Candidate preference (Trump vs. Clinton)   \n",
       "45       Vote for and evaluation of Trump and Clinton   \n",
       "50                                     Vote for Trump   \n",
       "52                                     Vote for Trump   \n",
       "54  Vote for six Democratic candidates (including ...   \n",
       "55                          Vote for Trump and Romney   \n",
       "57                                     Vote for Trump   \n",
       "58  Preference for Trump and Clinton (among non-vo...   \n",
       "59  Candidate evaluation (including Biden, Harris,...   \n",
       "60  Vote for presidential candidates (including Ob...   \n",
       "61  Attitudes towards real female or male candidat...   \n",
       "66  Voter turnout\\nEngagement with political campa...   \n",
       "69                         Voting for Romney or Obama   \n",
       "71                                     Vote for Biden   \n",
       "72  Evaluations of Biden and Trump (competence, mo...   \n",
       "74  Vote for a fictitious female candidate in stat...   \n",
       "75  Mid-term approval for Trump\\nEmotional affect ...   \n",
       "76                                     Vote for Trump   \n",
       "79  Feelings towards candidates (including Clinton...   \n",
       "82  Ambivalent attitudes toward candidates (Trump ...   \n",
       "90                                   Vote for Clinton   \n",
       "94  Support for Trump/Clinton\\nSupport for real an...   \n",
       "\n",
       "                                      Sexism concepts  \\\n",
       "1                                       Modern sexism   \n",
       "5                   Benevolent sexism\\nHostile sexism   \n",
       "10  Benevolent sexism \\nHostile sexism \\nBenevolen...   \n",
       "12                                      Modern sexism   \n",
       "14  Ambivalent sexism\\nBenevolent sexism\\nHostile ...   \n",
       "15                  Benevolent sexism\\nHostile sexism   \n",
       "17                                      Modern sexism   \n",
       "18                                     Hostile sexism   \n",
       "19                                      Modern sexism   \n",
       "21                                      Modern sexism   \n",
       "23                                     Hostile sexism   \n",
       "24                                      Modern sexism   \n",
       "25                      Hostile sexism\\nModern sexism   \n",
       "26                   Explicit sexism\\nImplicit sexism   \n",
       "27          Politically defined\\nDomestically defined   \n",
       "28                      Hostile sexism\\nModern sexism   \n",
       "29                  Benevolent sexism\\nHostile sexism   \n",
       "30                  Benevolent sexism\\nHostile sexism   \n",
       "32                  Benevolent sexism\\nHostile sexism   \n",
       "33                                      Modern sexism   \n",
       "34                  Modern sexism\\nTraditional sexism   \n",
       "36                  Benevolent sexism\\nHostile sexism   \n",
       "37                                     Hostile sexism   \n",
       "43                                      Modern sexism   \n",
       "44   Benevolent sexism\\nHostile sexism\\nModern sexism   \n",
       "45                  Benevolent sexism\\nHostile sexism   \n",
       "50                                             Sexism   \n",
       "52                                             Sexism   \n",
       "54                                     Hostile sexism   \n",
       "55              Sexism\\nHostile sexism\\nModern sexism   \n",
       "57                                      Modern sexism   \n",
       "58                                  Ambivalent sexism   \n",
       "59                      Hostile sexism\\nModern sexism   \n",
       "60                  Benevolent sexism\\nHostile sexism   \n",
       "61                                             Sexism   \n",
       "66                                     Hostile sexism   \n",
       "69                           Neosexism\\nImplicit bias   \n",
       "71                                      Modern sexism   \n",
       "72                                      Modern sexism   \n",
       "74                                      Modern sexism   \n",
       "75                                      Modern sexism   \n",
       "76                  Modern sexism\\nTraditional sexism   \n",
       "79                      Hostile sexism\\nModern sexism   \n",
       "82                                             Sexism   \n",
       "90                                      Modern sexism   \n",
       "94                  Hostile sexism\\nBenevolent sexism   \n",
       "\n",
       "                                         Sexism items  \\\n",
       "1   \"1) whether they believe that women miss out o...   \n",
       "5   Full Ambivalent Sexism Inventory (Glick and Fi...   \n",
       "10  Full Ambivalent Sexism Inventory (Glick and Fi...   \n",
       "12  ANES 2012:\\n\"How serious a problem is discrimi...   \n",
       "14  Full Ambivalent Sexism Inventory (Glick and Fi...   \n",
       "15  Full Ambivalent Sexism Inventory (Glick and Fi...   \n",
       "17  Denial of gender discrimination:\\n\"How serious...   \n",
       "18  \"Women fail to appreciate what men do for them...   \n",
       "19  \"Discrimination against women is no longer a p...   \n",
       "21  \"1. Discrimination against women is no longer ...   \n",
       "23  \"1. Women are too easily offended.\\n2. Many wo...   \n",
       "24  1) \"How much discrimination is there in the Un...   \n",
       "25  Hostile sexism:\\n1) Many women are actually se...   \n",
       "26  Explicit (Yes or No):\\n\"America is ready for a...   \n",
       "27  Political: \"Do you agree or disagree with the ...   \n",
       "28  Hostile sexism:\\n1) Do women demanding equalit...   \n",
       "29  Full Ambivalent Sexism Scale (Glick and Fiske ...   \n",
       "30  Full Ambivalent Sexism Scale (Glick and Fiske ...   \n",
       "32  Hostile:\\nWomen seek to gain power by getting ...   \n",
       "33  Full Modern Sexism Scale (Swim et al. 1995), 8...   \n",
       "34  Modern sexism:\\n\"(1) how much attention the me...   \n",
       "36  Study 1:\\nSix items on hostile sexism\\nSix ite...   \n",
       "37  (1) \"many women interpret innocent remarks as ...   \n",
       "43  \"modern sexism scale, and feelings about the A...   \n",
       "44  Full ASI scale (Glick and Fiske 1996)\\nFull mo...   \n",
       "45              Full ASI scale (Glick and Fiske 1996)   \n",
       "50  In Appendix E, not found online.\\n\\n\"We produc...   \n",
       "52  CCES\\n1) _x0007_Women should earn the same wag...   \n",
       "54  4 items from ANES, i.e.:\\n\"(1) \"many women int...   \n",
       "55  1. Media should pay less attention to discrimi...   \n",
       "57  \"1. Many women are actually seeking special fa...   \n",
       "58  \"1. ‘Many women interpret innocent remarks or ...   \n",
       "59  6 hostile sexism items \"reflects ANES\"\\n1 mode...   \n",
       "60              Full ASI scale (Glick and Fiske 2001)   \n",
       "61  \"Women should return to their traditional role...   \n",
       "66  (1) \"many women interpret innocent remarks as ...   \n",
       "69  Implicit: evaluative priming paradigm\\n\\nExpli...   \n",
       "71  \"Difference between perceptions of discriminat...   \n",
       "72  \"eight items that measured denial of continuin...   \n",
       "74  \"(1) how much discrimination they believe wome...   \n",
       "75  \"Resentment of feminism\"\\n(1) \"When women lose...   \n",
       "76  Modern sexism:\\n\"1. When women demand equality...   \n",
       "79  \"Hostile Sexism\\nOnce a woman gets a man to co...   \n",
       "82  ANES 1992-2000:\\ncloser to the equal role (1) ...   \n",
       "90  Original SSI (items from ASI, but directly ref...   \n",
       "94  \"Benevolent Sexism\\n1. Many women have a quali...   \n",
       "\n",
       "                                        Main findings  \\\n",
       "1   \"Sexism […] did not significantly influence ev...   \n",
       "5   \"participant gender, benevolent sexism, hostil...   \n",
       "10  \"The finding that greater resentment of patern...   \n",
       "12  \"mass assessments of Hillary Clinton were shap...   \n",
       "14  \"Ambivalent sexism was the strongest predictor...   \n",
       "15  \"After controlling for participant sex, time o...   \n",
       "17  \"a denial of gender discrimination problems cr...   \n",
       "18  \"Among white women, ambivalent sexist views po...   \n",
       "19  \"Individuals who perceived sexism to be more p...   \n",
       "21  \"Results indicated that women’s gender-related...   \n",
       "23  \"racial attitudes and sexism were much more st...   \n",
       "24  \"although party affiliation was an important p...   \n",
       "25  \"2016 was the only year in which [sexism] play...   \n",
       "26  \"The analysis reveals that even after controll...   \n",
       "27  \"politically defined […] sexism […] predicts s...   \n",
       "28  \"white women endorse sexist beliefs, and that ...   \n",
       "29  \"hostile sexists exposed to the [Trump’s \"woma...   \n",
       "30  \"benevolent (and not hostile) sexism predicted...   \n",
       "32  \"Hostile sexist attitudes were second only to ...   \n",
       "33  \"Although Clinton matched the ideal better tha...   \n",
       "34  \"Both modern and traditional sexism were signi...   \n",
       "36  \"greater hostile sexism predicted more positiv...   \n",
       "37  \"Greater conservatism or sexism significantly ...   \n",
       "43  Sexism did not predict vote for Trump in the p...   \n",
       "44  \"Controlling for conservatism, we found that (...   \n",
       "45  \"Sexism toward women and U.S. nationalism were...   \n",
       "50  \"The effects of racial resentment and sexism w...   \n",
       "52  a \"profile—an amalgamation of attitudes about,...   \n",
       "54  \"Study 1 found deleterious effects of hostile ...   \n",
       "55  \"Sexist orientations had a greater impact on h...   \n",
       "57  Modern sexism was a significant predictor of v...   \n",
       "58  Ambivalent sexism coefficient is not statistic...   \n",
       "59  \"Using a survey of self-identified Democrats, ...   \n",
       "60  \"Although benevolent sexism was a significant ...   \n",
       "61  Sexism is a negative predictor of favorability...   \n",
       "66  Hostile sexism proved demobilizing for Democra...   \n",
       "69  \"we observed that measures of implicit bias ar...   \n",
       "71  \"we find that respondents with moderate levels...   \n",
       "72  Modern sexism predicted favorability toward Tr...   \n",
       "74  \"when a male candidate attempts to activate se...   \n",
       "75  \"adherence to the tenets of American civil rel...   \n",
       "76  \"While Latinxs do express higher levels of sex...   \n",
       "79  \"We find that among Democrats, hostile sexists...   \n",
       "82  attitudinal ambivalence toward female candidat...   \n",
       "90  \"Concerns that women are trying to dominate me...   \n",
       "94  Hostile and benevolent sexism increase support...   \n",
       "\n",
       "      Theoretical mechanism linking sexism to outcome Ambivalent sexism  \\\n",
       "1   \"it is possible that Palin’s and Obama’s prese...               NaN   \n",
       "5   Role congruity theory:\\n\"role congruity theory...               NaN   \n",
       "10  \"removing the benevolence toward men construct...               NaN   \n",
       "12  \"Modern sexists, who believe women are receivi...               NaN   \n",
       "14                                                NaN        Ambivalent   \n",
       "15                                                NaN               NaN   \n",
       "17  Expect stronger effects among men because:\\n1)...               NaN   \n",
       "18  system justifying ideologies:\\n\"interdependenc...               NaN   \n",
       "19  \"female politicians are judged based on gender...               NaN   \n",
       "21  \"Women who perceive discrimination as a pervas...               NaN   \n",
       "23  Explicit focus in Trump's rhetoric on race and...               NaN   \n",
       "24                                                NaN               NaN   \n",
       "25  \"an outwardly feminist, female candidate was r...               NaN   \n",
       "26  \"The prospect of a woman serving as president ...               NaN   \n",
       "27  \"We argue that the 2016 election implicated ge...               NaN   \n",
       "28  Intersectionality and system justification:\\n\"...               NaN   \n",
       "29  System justification theory:\\n\"Trump’s attacks...               NaN   \n",
       "30  \"Reflecting shifting standards (a tendency to ...               NaN   \n",
       "32  Sexism stems from male dominance, so both host...               NaN   \n",
       "33  \"Modern Sexism might exacerbate demands to fit...               NaN   \n",
       "34  \"the mere presence of a woman running for the ...               NaN   \n",
       "36  Hostile sexists dislike women who break the st...               NaN   \n",
       "37  \"if sexism influenced voters' decisions, left-...               NaN   \n",
       "43  \"More important is the fact that there was lit...               NaN   \n",
       "44                                                NaN               NaN   \n",
       "45                                                NaN               NaN   \n",
       "50                                                NaN               NaN   \n",
       "52                                                NaN               NaN   \n",
       "54  \"Voters may hold male and female candidates to...               NaN   \n",
       "55                                                NaN               NaN   \n",
       "57                                                NaN               NaN   \n",
       "58                                                NaN        Ambivalent   \n",
       "59  \"heuristic search\"\\n\"Campaigns’ emphases on ge...               NaN   \n",
       "60                                                NaN               NaN   \n",
       "61                                                NaN               NaN   \n",
       "66  \"For Democrats, high levels of hostile sexism ...               NaN   \n",
       "69                                                NaN               NaN   \n",
       "71  \"mention of Harris will make gender priors sal...               NaN   \n",
       "72                                                NaN               NaN   \n",
       "74  Standard political communication framework: \"a...               NaN   \n",
       "75  \"we contend that the confluence of civil relig...               NaN   \n",
       "76  \"Absent meaningful conceptual differences betw...               NaN   \n",
       "79  \"citizens’ gender-relevant attitudes, in conju...               NaN   \n",
       "82  \"Individuals who hold sexist attitudes should ...               NaN   \n",
       "90  \"we expect sexism directed against feminists, ...               NaN   \n",
       "94  1) Hostile sexism is directed at women who see...               NaN   \n",
       "\n",
       "   Benevolent sexism Hostile sexism Modern sexism  Neosexism  \\\n",
       "1                NaN            NaN        Modern        NaN   \n",
       "5         Benevolent        Hostile           NaN        NaN   \n",
       "10        Benevolent        Hostile           NaN        NaN   \n",
       "12               NaN            NaN        Modern        NaN   \n",
       "14        Benevolent        Hostile           NaN        NaN   \n",
       "15        Benevolent        Hostile           NaN        NaN   \n",
       "17               NaN            NaN        Modern        NaN   \n",
       "18               NaN        Hostile           NaN        NaN   \n",
       "19               NaN            NaN        Modern        NaN   \n",
       "21               NaN            NaN        Modern        NaN   \n",
       "23               NaN        Hostile           NaN        NaN   \n",
       "24               NaN            NaN        Modern        NaN   \n",
       "25               NaN        Hostile        Modern        NaN   \n",
       "26               NaN            NaN           NaN        NaN   \n",
       "27               NaN            NaN           NaN        NaN   \n",
       "28               NaN        Hostile        Modern        NaN   \n",
       "29        Benevolent        Hostile           NaN        NaN   \n",
       "30        Benevolent        Hostile           NaN        NaN   \n",
       "32        Benevolent        Hostile           NaN        NaN   \n",
       "33               NaN            NaN        Modern        NaN   \n",
       "34               NaN            NaN        Modern        NaN   \n",
       "36        Benevolent        Hostile           NaN        NaN   \n",
       "37               NaN        Hostile           NaN        NaN   \n",
       "43               NaN            NaN        Modern        NaN   \n",
       "44        Benevolent        Hostile        Modern        NaN   \n",
       "45        Benevolent        Hostile           NaN        NaN   \n",
       "50               NaN            NaN           NaN        NaN   \n",
       "52               NaN            NaN           NaN        NaN   \n",
       "54               NaN        Hostile           NaN        NaN   \n",
       "55               NaN        Hostile        Modern        NaN   \n",
       "57               NaN            NaN        Modern        NaN   \n",
       "58               NaN            NaN           NaN        NaN   \n",
       "59               NaN        Hostile        Modern        NaN   \n",
       "60        Benevolent        Hostile           NaN        NaN   \n",
       "61               NaN            NaN           NaN        NaN   \n",
       "66               NaN        Hostile           NaN        NaN   \n",
       "69               NaN            NaN           NaN  Neosexism   \n",
       "71               NaN            NaN        Modern        NaN   \n",
       "72               NaN            NaN        Modern        NaN   \n",
       "74               NaN            NaN        Modern        NaN   \n",
       "75               NaN            NaN        Modern        NaN   \n",
       "76               NaN            NaN        Modern        NaN   \n",
       "79               NaN        Hostile        Modern        NaN   \n",
       "82               NaN            NaN           NaN        NaN   \n",
       "90               NaN            NaN        Modern        NaN   \n",
       "94        Benevolent        Hostile           NaN        NaN   \n",
       "\n",
       "                                          concept_low  \n",
       "1                                       modern sexism  \n",
       "5                   benevolent sexism\\nhostile sexism  \n",
       "10  benevolent sexism \\nhostile sexism \\nbenevolen...  \n",
       "12                                      modern sexism  \n",
       "14  ambivalent sexism\\nbenevolent sexism\\nhostile ...  \n",
       "15                  benevolent sexism\\nhostile sexism  \n",
       "17                                      modern sexism  \n",
       "18                                     hostile sexism  \n",
       "19                                      modern sexism  \n",
       "21                                      modern sexism  \n",
       "23                                     hostile sexism  \n",
       "24                                      modern sexism  \n",
       "25                      hostile sexism\\nmodern sexism  \n",
       "26                   explicit sexism\\nimplicit sexism  \n",
       "27          politically defined\\ndomestically defined  \n",
       "28                      hostile sexism\\nmodern sexism  \n",
       "29                  benevolent sexism\\nhostile sexism  \n",
       "30                  benevolent sexism\\nhostile sexism  \n",
       "32                  benevolent sexism\\nhostile sexism  \n",
       "33                                      modern sexism  \n",
       "34                  modern sexism\\ntraditional sexism  \n",
       "36                  benevolent sexism\\nhostile sexism  \n",
       "37                                     hostile sexism  \n",
       "43                                      modern sexism  \n",
       "44   benevolent sexism\\nhostile sexism\\nmodern sexism  \n",
       "45                  benevolent sexism\\nhostile sexism  \n",
       "50                                             sexism  \n",
       "52                                             sexism  \n",
       "54                                     hostile sexism  \n",
       "55              sexism\\nhostile sexism\\nmodern sexism  \n",
       "57                                      modern sexism  \n",
       "58                                  ambivalent sexism  \n",
       "59                      hostile sexism\\nmodern sexism  \n",
       "60                  benevolent sexism\\nhostile sexism  \n",
       "61                                             sexism  \n",
       "66                                     hostile sexism  \n",
       "69                           neosexism\\nimplicit bias  \n",
       "71                                      modern sexism  \n",
       "72                                      modern sexism  \n",
       "74                                      modern sexism  \n",
       "75                                      modern sexism  \n",
       "76                  modern sexism\\ntraditional sexism  \n",
       "79                      hostile sexism\\nmodern sexism  \n",
       "82                                             sexism  \n",
       "90                                      modern sexism  \n",
       "94                  hostile sexism\\nbenevolent sexism  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Number of papers on presidential or primary elections:\",len(df[df['Elections (if any)'].fillna(value='0').str.contains('residential|rimar')]))\n",
    "print(\"Number of papers on presidential or primary elections, not including Trump or Clinton:\",len(df[(df['Elections (if any)'].fillna(value='0').str.contains('residential|rimar')) & (~df['Outcome variables'].str.contains('Trump')) & (~df['Outcome variables'].str.contains('Clinton'))]))\n",
    "\n",
    "# df[(df['Elections (if any)'].fillna(value='0').str.contains('residential|rimar')) & (~df['Outcome variables'].str.contains('Trump'))] # & (~df['Outcome variables'].str.contains('Clinton'))]\n",
    "df[(df['Elections (if any)'].fillna(value='0').str.contains('residential|rimar')) & (df['Countries under study'].astype(str).str.contains('USA'))]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cb8882ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 9600x5400 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grouping the data by 'Year' and 'Countries under study'\n",
    "df['USA'] = df['Countries under study'].str.contains('USA', na=False)\n",
    "\n",
    "# Counting occurrences per year for USA and non-USA\n",
    "year_counts = df.groupby(['Year', 'USA']).size().unstack(fill_value=0)\n",
    "year_counts.columns=pd.CategoricalIndex(year_counts.columns.values, ordered=True, categories=[True,False])\n",
    "\n",
    "# Plot with stacked bars\n",
    "colors = ['#56B4E9', '#E69F00']  # Blue = With USA, Orange = Without USA\n",
    "\n",
    "#Sort the data\n",
    "year_counts = year_counts.sort_index(axis=1)\n",
    "\n",
    "# Creating the stacked bar plot\n",
    "plt.figure(figsize=(16, 9), facecolor='white', dpi=600)\n",
    "ax = year_counts.plot(kind='bar', stacked=True, color=colors, edgecolor='black')  # Colorblind-safe\n",
    "\n",
    "\n",
    "# Add hatching patterns to bars\n",
    "patterns = ['//', '\\\\\\\\']\n",
    "for bars, pattern in zip(ax.containers, patterns):\n",
    "    for bar in bars:\n",
    "        bar.set_hatch(pattern)\n",
    "\n",
    "# Adding labels and title\n",
    "plt.xlabel('Year', fontsize=14)\n",
    "plt.ylabel('Number of publications', fontsize=14)\n",
    "\n",
    "# Rotating x-axis labels\n",
    "plt.xticks(rotation=45)\n",
    "plt.yticks(range(0, max(year_counts.sum(axis=1)) + 2, 2))\n",
    "\n",
    "# Customizing grid lines\n",
    "plt.grid(axis='y', linestyle='-', alpha=0.2)\n",
    "\n",
    "# Removing unnecessary spines\n",
    "plt.gca().spines['top'].set_visible(False)\n",
    "plt.gca().spines['right'].set_visible(False)\n",
    "\n",
    "# Adding legend\n",
    "\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "labels = ['With USA','Without USA']\n",
    "ax.legend(handles[::-1], labels[::-1], loc='upper left')\n",
    "# plt.legend(labels[::-1], loc='upper left')\n",
    "\n",
    "# Displaying the plot\n",
    "plt.tight_layout()\n",
    "plt.savefig('Frequencies plot, stacked USA.png', dpi=600, facecolor='white')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a24f2fb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Countries under study</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1997</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010</td>\n",
       "      <td>New Zealand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2011</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2011</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2012</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014</td>\n",
       "      <td>New Zealand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2016</td>\n",
       "      <td>New Zealand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2016</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2017</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2017</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2017</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2017</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2017</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2018</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2018</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Year Countries under study\n",
       "0   1997                   USA\n",
       "1   2009                   USA\n",
       "2   2009                   USA\n",
       "3   2010                Canada\n",
       "4   2010           New Zealand\n",
       "5   2011                   USA\n",
       "6   2011                   USA\n",
       "7   2012                   USA\n",
       "8   2014           New Zealand\n",
       "9   2014                 Italy\n",
       "10  2014                   USA\n",
       "11  2016           New Zealand\n",
       "12  2016                   USA\n",
       "13  2017                   USA\n",
       "14  2017                   USA\n",
       "15  2017                   USA\n",
       "16  2017                   USA\n",
       "17  2017                   USA\n",
       "18  2018                   USA\n",
       "19  2018                   USA"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the values from the plot with the first 20 papers\n",
    "\n",
    "df[['Year','Countries under study']].head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f65d7970",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common words longer than 1 character in dfx['Author']:\n",
      "danny: 5\n",
      "erin: 5\n",
      "osborne: 4\n",
      "davies: 4\n",
      "paul: 4\n",
      "cassese: 4\n",
      "elizabeth: 4\n",
      "matthew: 4\n",
      "sibley: 3\n",
      "chris: 3\n",
      "barnes: 3\n",
      "tiffany: 3\n",
      "schaffner: 3\n",
      "brian: 3\n",
      "nicholas: 3\n",
      "holman: 3\n",
      "mirya: 3\n",
      "anne: 3\n",
      "archer: 3\n",
      "allison: 3\n",
      "beauregard: 3\n",
      "katrine: 3\n",
      "amanda: 3\n",
      "filindra: 3\n",
      "alexandra: 3\n",
      "glenn: 2\n",
      "john: 2\n",
      "ryan: 2\n",
      "amy: 2\n",
      "bettina: 2\n",
      "michelle: 2\n",
      "huang: 2\n",
      "yanshu: 2\n",
      "karen: 2\n",
      "jennifer: 2\n",
      "melissa: 2\n",
      "prusaczyk: 2\n",
      "elvira: 2\n",
      "hodson: 2\n",
      "gordon: 2\n",
      "valentino: 2\n",
      "wayne: 2\n",
      "carly: 2\n",
      "oceno: 2\n",
      "marzia: 2\n",
      "rachel: 2\n",
      "brittany: 2\n",
      "godbole: 2\n",
      "maya: 2\n",
      "malvar: 2\n",
      "noelle: 2\n",
      "valian: 2\n",
      "virginia: 2\n",
      "jonathan: 2\n",
      "kam: 2\n",
      "cindy: 2\n",
      "costa: 2\n",
      "mia: 2\n",
      "thomas: 2\n",
      "patricia: 2\n",
      "sheppard: 2\n",
      "jill: 2\n",
      "buyuker: 2\n",
      "beyza: 2\n",
      "kaplan: 2\n",
      "noah: 2\n",
      "andrew: 2\n",
      "kevin: 2\n",
      "hayes: 2\n",
      "hickel: 2\n",
      "flavio: 2\n",
      "banducci: 2\n",
      "susan: 2\n",
      "campbell: 1\n",
      "bernadette: 1\n",
      "schellenberg: 1\n",
      "senn: 1\n",
      "charlene: 1\n",
      "dwyer: 1\n",
      "caitlin: 1\n",
      "stevens: 1\n",
      "daniel: 1\n",
      "sullivan: 1\n",
      "allen: 1\n",
      "barbara: 1\n",
      "rye: 1\n",
      "meaney: 1\n",
      "perry: 1\n",
      "gervais: 1\n",
      "sarah: 1\n",
      "hillard: 1\n",
      "schlehofer: 1\n",
      "michèle: 1\n",
      "casad: 1\n",
      "bligh: 1\n",
      "grotto: 1\n",
      "angela: 1\n",
      "russo: 1\n",
      "silvia: 1\n",
      "rutto: 1\n",
      "filippo: 1\n",
      "mosso: 1\n",
      "cristina: 1\n",
      "tate: 1\n",
      "charlotte: 1\n",
      "chuck: 1\n",
      "mcthomas: 1\n",
      "mary: 1\n",
      "tesler: 1\n",
      "michael: 1\n",
      "blair: 1\n",
      "bock: 1\n",
      "jarrod: 1\n",
      "burkley: 1\n",
      "ruthig: 1\n",
      "joelle: 1\n",
      "kehn: 1\n",
      "andre: 1\n",
      "gamblin: 1\n",
      "bradlee: 1\n",
      "vanderzanden: 1\n",
      "jones: 1\n",
      "kelly: 1\n",
      "simas: 1\n",
      "bumgardner: 1\n",
      "marcia: 1\n",
      "lorrie: 1\n",
      "lytle: 1\n",
      "ashley: 1\n",
      "macdonald: 1\n",
      "jamie: 1\n",
      "dyar: 1\n",
      "christina: 1\n",
      "levy: 1\n",
      "sheri: 1\n",
      "mcmahon: 1\n",
      "jean: 1\n",
      "kahn: 1\n",
      "kimberly: 1\n",
      "barsamian: 1\n",
      "pahlke: 1\n",
      "bigler: 1\n",
      "rebecca: 1\n",
      "patterson: 1\n",
      "meagan: 1\n",
      "macwilliams: 1\n",
      "nteta: 1\n",
      "tatishe: 1\n",
      "setzler: 1\n",
      "mark: 1\n",
      "yanus: 1\n",
      "alixandra: 1\n",
      "barnello: 1\n",
      "bitecofer: 1\n",
      "kidd: 1\n",
      "quentin: 1\n",
      "bracic: 1\n",
      "ana: 1\n",
      "mackenzie: 1\n",
      "shortle: 1\n",
      "allyson: 1\n",
      "cassidy: 1\n",
      "krendl: 1\n",
      "ditonto: 1\n",
      "tessa: 1\n",
      "glick: 1\n",
      "peter: 1\n",
      "knuckey: 1\n",
      "lodders: 1\n",
      "vanna: 1\n",
      "weldon: 1\n",
      "steven: 1\n",
      "ratliff: 1\n",
      "kate: 1\n",
      "redford: 1\n",
      "liz: 1\n",
      "conway: 1\n",
      "smith: 1\n",
      "colin: 1\n",
      "tucker: 1\n",
      "rothwell: 1\n",
      "valerie: 1\n",
      "beaulieu: 1\n",
      "emily: 1\n",
      "saxton: 1\n",
      "gregory: 1\n",
      "batista: 1\n",
      "pereira: 1\n",
      "frederico: 1\n",
      "porto: 1\n",
      "nathália: 1\n",
      "briggs: 1\n",
      "trevor: 1\n",
      "chahal: 1\n",
      "ajaipal: 1\n",
      "fried: 1\n",
      "garg: 1\n",
      "rijul: 1\n",
      "kriz: 1\n",
      "sophia: 1\n",
      "lei: 1\n",
      "leo: 1\n",
      "milne: 1\n",
      "anthony: 1\n",
      "slayton: 1\n",
      "jennah: 1\n",
      "druckman: 1\n",
      "james: 1\n",
      "sharrow: 1\n",
      "ferguson: 1\n",
      "page: 1\n",
      "benjamin: 1\n",
      "rothschild: 1\n",
      "jacob: 1\n",
      "chang: 1\n",
      "arturo: 1\n",
      "chen: 1\n",
      "jie: 1\n",
      "monteith: 1\n",
      "margo: 1\n",
      "hildebrand: 1\n",
      "laura: 1\n",
      "shook: 1\n",
      "natalie: 1\n",
      "fitzgerald: 1\n",
      "holly: 1\n",
      "boggs: 1\n",
      "shelby: 1\n",
      "ford: 1\n",
      "cameron: 1\n",
      "hopkins: 1\n",
      "silva: 1\n",
      "nicole: 1\n",
      "bai: 1\n",
      "hui: 1\n",
      "benegal: 1\n",
      "salil: 1\n",
      "durso: 1\n",
      "jadidi: 1\n",
      "enders: 1\n",
      "adam: 1\n",
      "uscinski: 1\n",
      "joseph: 1\n",
      "franks: 1\n",
      "hanley: 1\n",
      "eric: 1\n",
      "maxwell: 1\n",
      "angie: 1\n",
      "medenica: 1\n",
      "vladimir: 1\n",
      "fowler: 1\n",
      "nelson: 1\n",
      "kjersten: 1\n",
      "spencer: 1\n",
      "utych: 1\n",
      "stephen: 1\n",
      "ananyeva: 1\n",
      "olga: 1\n",
      "tatarenko: 1\n",
      "maria: 1\n",
      "anduiza: 1\n",
      "eva: 1\n",
      "rico: 1\n",
      "guillem: 1\n",
      "clifford: 1\n",
      "scott: 1\n",
      "baker: 1\n",
      "majel: 1\n",
      "mcclelland: 1\n",
      "sara: 1\n",
      "jozkowski: 1\n",
      "kristen: 1\n",
      "banda: 1\n",
      "bills: 1\n",
      "calvert: 1\n",
      "gemma: 1\n",
      "evans: 1\n",
      "geoffrey: 1\n",
      "pathak: 1\n",
      "abhishek: 1\n",
      "de: 1\n",
      "geus: 1\n",
      "roosmarijn: 1\n",
      "shorrocks: 1\n",
      "rosalind: 1\n",
      "fagan: 1\n",
      "grace: 1\n",
      "gothreau: 1\n",
      "claire: 1\n",
      "arceneaux: 1\n",
      "friesen: 1\n",
      "lawless: 1\n",
      "murphy: 1\n",
      "rogerio: 1\n",
      "deckman: 1\n",
      "jylhä: 1\n",
      "kirsti: 1\n",
      "rydgren: 1\n",
      "jens: 1\n",
      "strimling: 1\n",
      "pontus: 1\n",
      "lemi: 1\n",
      "danielle: 1\n",
      "casarez: 1\n",
      "long: 1\n",
      "meri: 1\n",
      "dawe: 1\n",
      "suhay: 1\n",
      "bauer: 1\n",
      "nichole: 1\n",
      "britzman: 1\n",
      "kylee: 1\n",
      "joel: 1\n",
      "cizmar: 1\n",
      "kalkan: 1\n",
      "kerem: 1\n",
      "ozan: 1\n",
      "coffe: 1\n",
      "hilde: 1\n",
      "fraile: 1\n",
      "marta: 1\n",
      "alexander: 1\n",
      "jessica: 1\n",
      "lee: 1\n",
      "longdon: 1\n",
      "bella: 1\n",
      "miura: 1\n",
      "mari: 1\n",
      "mcelwain: 1\n",
      "kenneth: 1\n",
      "mori: 1\n",
      "kaneko: 1\n",
      "tomoki: 1\n",
      "obreque: 1\n",
      "oviedo: 1\n",
      "cárdenas: 1\n",
      "castro: 1\n",
      "manuel: 1\n",
      "shortell: 1\n",
      "christopher: 1\n",
      "valdini: 1\n",
      "melody: 1\n",
      "verge: 1\n",
      "tània: 1\n",
      "tormos: 1\n",
      "raül: 1\n",
      "winter: 1\n",
      "léal: 1\n",
      "leblanc: 1\n",
      "juliette: 1\n",
      "taylor: 1\n",
      "vandewalle: 1\n",
      "virginie: 1\n",
      "dassonneville: 1\n",
      "ruth: 1\n",
      "russell: 1\n",
      "brenda: 1\n",
      "oswald: 1\n",
      "debra: 1\n",
      "cotter: 1\n",
      "marykate: 1\n"
     ]
    }
   ],
   "source": [
    "### Count number of papers per authors\n",
    "\n",
    "import string\n",
    "from collections import Counter\n",
    "import nltk\n",
    "from nltk.tokenize import word_tokenize\n",
    "\n",
    "\n",
    "# Tokenize and lowercase the text, excluding punctuation\n",
    "def preprocess_text(text):\n",
    "    text = text.lower()\n",
    "    tokens = word_tokenize(text)\n",
    "    return [token for token in tokens if token.isalpha()]\n",
    "\n",
    "# Combine all text into a single string\n",
    "all_text = ' '.join(df['Author'].astype(str))\n",
    "\n",
    "# Tokenize and preprocess the text\n",
    "words = preprocess_text(all_text)\n",
    "\n",
    "# Count the occurrences of each word\n",
    "word_counts = Counter(words)\n",
    "\n",
    "# Filter out words longer than 1 character and get the most common ones\n",
    "most_common_words = [(word, count) for word, count in word_counts.items() if len(word) > 1]\n",
    "\n",
    "# Sort the most common words by count\n",
    "most_common_words.sort(key=lambda x: x[1], reverse=True)\n",
    "\n",
    "print(\"Most common words longer than 1 character in dfx['Author']:\")\n",
    "for word, count in most_common_words:\n",
    "    print(f\"{word}: {count}\")\n"
   ]
  }
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